bluuebunny/crossref_metadata_2025_split huggingface dataset:
Inter- and Intra-observer Agreement of the Peripheral Arterial Calcium Scoring System in Patients Undergoing (Infra)Popliteal Endovascular Interventions
Authors: Nugteren Michael J. , Ünlü Çağdaş , Samim Morsal , Scheffer Hester J. , de Borst Gert J. , Hazenberg Constantijn E. V. B. 
Published: August 2024

Abstract
Purpose
Peripheral arterial calcification is an important predictor of outcomes after both conservative and endovascular treatment. Digital subtraction angiography (DSA)-based calcification scores are limited by low sensitivity and inter-observer agreement. The Peripheral Arterial Calcium Scoring System (PACSS) assesses the severity of target lesion calcification. The newly introduced modified PACSS (mPACSS) also evaluates target vessel calcification. This study aimed to assess the inter- and intra-observer reliability of PACSS and mPACSS on computed tomography angiography (CTA) in (infra)popliteal endovascular interventions.

Methods
A random sample of 50 limbs from the prospective multicenter Dutch Chronic Lower Limb-Threatening Ischemia Registry (THRILLER) were included. Three experienced independent raters scored PACSS on CTA. Three months later, one blinded rater assessed the same 50 CTA scans, keeping track of assessment time. The reliability of the original 5-step PACSS, a simplified binary PACSS (0–2 vs 3–4) and the 7-step mPACSS were tested using Cohen’s and Fleiss’ kappa statistics.

Results
In total, 50 limbs (mean age 70.1 ± 11.0, 29 men) with 41 popliteal and 40 infrapopliteal lesions were scored. Inter-observer agreement of PACSS and binary PACSS were moderate (κ = 0.60) and substantial (κ = 0.72), respectively, while intra-observer agreement was almost perfect in both scores (κ = 0.86). Inter- and intra-observer agreement of mPACSS were moderate (κ = 0.48) and substantial (κ = 0.77), respectively. Mean assessment time for an experienced rater was 3.43 ± 0.93 min per CTA scan.

Conclusion
Both the semi-quantitative PACSS and mPACSS scores for (infra)popliteal arteries can be performed reliably on pre-operative CTA.

Graphic Abstract
The mark of success: The role of vaccine-induced skin scar formation for BCG and smallpox vaccine-associated clinical benefits
Authors: Bæk Ole , Schaltz-Buchholzer Frederik , Campbell Anita , Amenyogbe Nelly , Campbell James , Aaby Peter , Benn Christine Stabell , Kollmann Tobias R. 
Published: August 2024

AbstractSkin scar formation following Bacille Calmette-Guérin (BCG) or smallpox (Vaccinia) vaccination is an established marker of successful vaccination and ‘vaccine take’. Potent pathogen-specific (tuberculosis; smallpox) and pathogen-agnostic (protection from diseases unrelated to the intentionally targeted pathogen) effects of BCG and smallpox vaccines hold significant translational potential. Yet despite their use for centuries, how scar formation occurs and how local skin-based events relate to systemic effects that allow these two vaccines to deliver powerful health promoting effects has not yet been determined. We review here what is known about the events occurring in the skin and place this knowledge in the context of the overall impact of these two vaccines on human health with a particular focus on maternal-child health.
Be prepared! Impact of structured video-assisted coaching on performance in a simulated bleeding exercise during laparoscopic surgery
Authors: Chatziisaak Dimitrios , Sparn Moritz , Krstic Daniel , Bauci Gabriele , Warschkow Réne , Brunner Walter , Schmied Bruno , Hahnloser Dieter , Bischofberger Stephan 
Published: August 2024

Abstract
Background
Bleeding during laparoscopic surgery is stressful and requires immediate efficient management. Skills for complication management are rarely trained. This study aims to investigate the impact of video-assisted coaching on laparoscopic skills acquisition and performance in emergency bleeding situations.

Methods
Participants faced simulated emergency scenarios during laparoscopy involving bleeding management in porcine aorta/kidney specimens. Four sequences were conducted over two days, with a structured video-assisted coaching provided between sequences. Performance was assessed using the Global Operative Assessment of Laparoscopic Skills (GOALS) score. The study involved 27 participants attending the advanced colorectal surgery module at the 40th Annual Davos Course in 2023.

Results
54 video sequences were analyzed. Structured video-assisted coaching improved the GOALS sum score by 0.36 (95%CI: 0.21–0.50, P < 0.001) in contrast to simple repetition (0.05 with 95%CI: −0.43 to 0.53, P = 0.826). This association was observed for depth of perception (P < 0.001), bimanual dexterity (P < 0.001), tissue handling (P < 0.001), overall performance (P < 0.001), and efficiency (P < 0.001). Autonomy did not significantly improve (P = 0.55). Findings were consistent regardless of age, gender, and overall laparoscopic experience of the participants. However, a weaker effect of structured video-assisted coaching was observed in participants with experience in laparoscopic surgery.

Conclusion
Structured video-assisted coaching improved performance in laparoscopic skills in complex and stress-inducing bleeding scenarios. The findings of this study support the incorporation of video-assisted coaching and complication management exercises into surgical training curricula.
Relationship between GPS-based community mobility data and orthopedic trauma admissions during the COVID-19 pandemic in Austria: a multicenter analysis
Authors: Jeremic Natasa , Widhalm Harald Kurt , Doering Kevin , Popp Domenik , Stark Matthias , Ower Cornelia , Rohit Arora , Boesenberg Roberto , Leithner Andreas , Nia Arastoo 
Published: August 2024

Summary
Objective
The main objective of this study was to examine the relationship between mobility patterns during the coronavirus disease 2019 (COVID-19) pandemic and orthopedic trauma patients in Austria. Utilizing global positioning system (GPS)-based mobility data, the attempt was to assess both the impact of COVID-19 lockdowns on reducing orthopedic trauma patients and the degree of compliance to the imposed movement restrictions.

Methods
This retrospective analysis included all patients (283,501) treated at 3 major level I trauma centers in Austria. Analyzed time periods were 1 January 2019 to 8 February 2021. Freely available GPS-based mobility data from Google and Apple Inc. was gathered.

Results
A moderate to strong correlation between the cumulative average outpatients and the assessed mobility index was observed for all cities (Google: r = 0.70 p < 0.001, 95% confidence interval, CI: 0.67–0.73; Apple: r = 0.64 p < 0.001, 95% CI: 0.61–0.67). A significant linear regression equation was found for Vienna (adjusted r2 = 0.48; F(1, 350) = 328,05; p < 0.01). During the first lockdown there was a drastic decline in mobility (up to −75.36%) and in numbers of orthopedic trauma outpatients (up to −64%, from 153 patients/day 2019 to 55 patients/day 2020) in comparison to the prepandemic era. The decline diminished as time passed.

Conclusion
Analyses of GPS-based mobility patterns show a correlation with trauma patient numbers. These findings can be used to develop prediction models, leading to better resource planning and public health policy, enhancing patient care and cost-effectiveness, especially in the event of future pandemics. Furthermore, the results suggest that compliance to mobility restrictions decreased over time during the COVID-19 pandemic, resulting in increased mobility and trauma patients.
The Fine-Tuned Large Language Model for Extracting the Progressive Bone Metastasis from Unstructured Radiology Reports
Authors: Kanemaru Noriko , Yasaka Koichiro , Fujita Nana , Kanzawa Jun , Abe Osamu 
Published: August 2024

AbstractEarly detection of patients with impending bone metastasis is crucial for prognosis improvement. This study aimed to investigate the feasibility of a fine-tuned, locally run large language model (LLM) in extracting patients with bone metastasis in unstructured Japanese radiology report and to compare its performance with manual annotation. This retrospective study included patients with “metastasis” in radiological reports (April 2018–January 2019, August–May 2022, and April–December 2023 for training, validation, and test datasets of 9559, 1498, and 7399 patients, respectively). Radiologists reviewed the clinical indication and diagnosis sections of the radiological report (used as input data) and classified them into groups 0 (no bone metastasis), 1 (progressive bone metastasis), and 2 (stable or decreased bone metastasis). The data for group 0 was under-sampled in training and test datasets due to group imbalance. The best-performing model from the validation set was subsequently tested using the testing dataset. Two additional radiologists (readers 1 and 2) were involved in classifying radiological reports within the test dataset for testing purposes. The fine-tuned LLM, reader 1, and reader 2 demonstrated an accuracy of 0.979, 0.996, and 0.993, sensitivity for groups 0/1/2 of 0.988/0.947/0.943, 1.000/1.000/0.966, and 1.000/0.982/0.954, and time required for classification (s) of 105, 2312, and 3094 in under-sampled test dataset (n = 711), respectively. Fine-tuned LLM extracted patients with bone metastasis, demonstrating satisfactory performance that was comparable to or slightly lower than manual annotation by radiologists in a noticeably shorter time.
Intelligent characteristic objects method (INCOME): a data knowledge-based multi-criteria decision analysis
Authors: Kizielewicz Bartłomiej , Shekhovtsov Andrii , Więckowski Jakub , Wątróbski Jarosław , Sałabun Wojciech 
Published: August 2024

AbstractMulti-criteria decision analysis (MCDA) methods are vital in assessing decision variants under multiple conditions. However, involving domain experts in developing decision models can be challenging and costly, necessitating more scalable and independent solutions. This paper introduces the intelligent characteristic objects method (INCOME), which combines the k-Nearest Neighbor (kNN) algorithm and the COMET method to create a theoretical decision-maker for comparing characteristic objects (COs). INCOME overcomes limitations of classical MCDA methods, such as the TOPSIS approach, which struggles with complex functions and non-monotonic modeling. INCOME influences data-based knowledge to provide a robust framework for assessing decision options. The integration of the COMET method and kNN algorithm enables improved modeling of decision functions based on evaluated data, increasing the flexibility and independence of the INCOME approach. A case study assessing gas power plants based on four criteria is presented to validate the performance of the INCOME method. The results demonstrate high correlations with the reference model and slightly higher classical approaches like TOPSIS and TOPSIS-COMET. However, INCOME exhibits greater stability and flexibility by utilizing all available data instead of relying on limited expert knowledge. The proposed INCOME approach offers several advantages, including creating a continuous decision model, resistance to the Rank-Reversal phenomenon, and the potential for replacing domain experts with artificial experts. This study highlights the effectiveness of INCOME in Multi-Criteria Decision Analysis. It suggests future research directions, such as parameter selection and testing in different decision-making problems.
Extending the IMQ Model: Deep Characterization of the Human TLR7 Response for Early Drug Development
Authors: van den Noort Juliette A. , Assil Salma , Ronner Micha N. , Osse Michelle , Pot Iris , Yavuz Yalçin , Damman Jeffrey , Lubberts Erik , Rissmann Robert , der Kolk Tessa Niemeyer-van , Tomljanovic Ingrid , Jansen Manon A. A. , Moerland Matthijs 
Published: August 2024

Abstract
Imiquimod (IMQ; brand name Aldara®) is a registered topical agent that has been proven to induce local inflammation via the Toll-like receptor (TLR)7 pathway. The purpose of this study was to characterize TLR7-mediated inflammation following 7 days (168 h) of topical IMQ exposure in healthy volunteers, and to compare the effects of short exposure (48 h-72 h) with prolonged exposure (120 h-168 h). IMQ (100mg) was applied under occlusion to 5 different tape-stripped treatment sites on the back of 10 healthy participants for a maximum of 7 consecutive days. Erythema and skin perfusion were measured daily up to 168h. Biopsies for immunohistochemical staining and RNA sequencing were collected at 0h, 48h, 72h, 120h and 168h post IMQ application. IMQ triggered an inflammatory response starting at 48h after application, including erythema and perfusion of the skin. At the transcriptomic level, IMQ induced TLR7 signalling, IRF involvement and activation of TNF signalling via NF-κB. Furthermore, an enhanced inflammatory response at the cellular level was observed after prolonged IMQ exposure, with cellular infiltration of dendritic cells, macrophages and T cells which was also corroborated by transcriptomic profiles. No difference was found in the erythema and perfusion response after 168h of IMQ exposure compared to 72h. Prolonged IMQ exposure revealed enhanced cellular responses and additional pathways with modulated activity compared to short exposure and can therefore be of interest as a model for investigational compounds targeting innate and adaptive immune responses.
Core allocation to minimize total flow time in a multicore system in the presence of a processing time constraint
Authors: Vesilo Rein 
Published: August 2024

AbstractData centers are a vital and fundamental infrastructure component of the cloud. The requirement to execute a large number of demanding jobs places a premium on processing capacity. Parallelizing jobs to run on multiple cores reduces execution time. However, there is a decreasing marginal benefit to using more cores, with the speedup function quantifying the achievable gains. A critical performance metric is flow time. Previous results in the literature derived closed-form expressions for the optimal allocation of cores to minimize total flow time for a power-law speedup function if all jobs are present at time 0. However, this work did not place a constraint on the makespan. For many diverse applications, fast response times are essential, and latency targets are specified to avoid adverse impacts on user experience. This paper is the first to determine the optimal core allocations for a multicore system to minimize total flow time in the presence of a completion deadline (where all jobs have the same deadline). The allocation problem is formulated as a nonlinear optimization program that is solved using the Lagrange multiplier technique. Closed-form expressions are derived for the optimal core allocations, total flow time, and makespan, which can be fitted to a specified deadline by adjusting the value of a single Lagrange multiplier. Compared to the unconstrained problem, the shortest job first property for optimal allocation is maintained; however, a number of other properties require revising and other properties are only retained in a modified form (such as the scale-free and size-dependence properties). It is found that with a completion deadline the optimal solution may contain groups of simultaneous completions. In general, all possible patterns of single- and group-completion need to be considered, producing an exponential search space. However, the paper determines analytically that the optimal completion pattern consists of a sequence of single completions followed by a single group of simultaneous completions at the end, which reduces the search space dimension to being linear. The paper validates the Lagrange multiplier approach by verifying constraint qualifications.
Distinct In Vitro Differentiation Protocols Differentially Affect Cytotoxicity Induced by Heavy Metals in Human Neuroblastoma SH-SY5Y Cells
Authors: Ferdous Jannatul , Naitou Kiyotada , Shiraishi Mitsuya 
Published: August 2024

AbstractThe SH-SY5Y cell line is widely used in neurotoxicity studies. However, the effects of inducing cell differentiation on the cytotoxic effects of heavy metals are unclear. Therefore, we investigated the effects of mercuric chloride (HgCl2), cadmium chloride (CdCl2), arsenic trioxide (As2O3), and methylmercury (MeHg) on SH-SY5Y cells differentiated in the presence of insulin-like growth factor-I (IGF-I) or all-trans retinoic acid (ATRA). Neurite outgrowth with distinct changes in neuronal marker expression, phenotype, and cell cycle was induced in SH-SY5Y cells by IGF-I treatment for 1 day or ATRA treatment for up to 7 days. The cytotoxic effects of HgCl2 decreased at lower concentrations and increased at higher concentrations in both IGF-I- and ATRA-differentiated cells compared with those in undifferentiated cells. Differentiation with IGF-I, but not with ATRA, increased the cytotoxic effects of CdCl2. Decreased cytotoxic effects of As2O3 and MeHg were observed at lower concentrations in IGF-I-differentiated cells, whereas increased cytotoxic effects of As2O3 and MeHg were observed at higher concentrations in ATRA-differentiated cells. Changes in the cytotoxic effects of heavy metals were observed even after 1 day of ATRA exposure in SH-SY5Y cells. Our results demonstrate that the differentiation of SH-SY5Y cells by IGF-I and ATRA induces different cellular characteristics, resulting in diverse changes in sensitivity to heavy metals, which depend not only on the differentiation agents and treatment time but also on the heavy metal species and concentration.
Source Identification Using Principal Component Analysis and Health Risk Assessment of Heavy Metals Contamination in PM2.5 Near an Industrial Area in Thailand
Authors: Simatupang Cathleen Ariella , Santhaweesuk Kanitthika , Pongkiatkul Prapat , Strezov Vladimir , Boontanon Narin , Jindal Ranjna , Boontanon Suwanna Kitpati 
Published: August 2024

Abstract
Industrialization has led to a surge in air pollution-related problems, as particulate matter (PM) containing heavy metals poses significant health risks. Understanding airborne particle chemistry, particularly the presence of heavy metals, is vital for effective air quality management and health interventions. This study analysed heavy metal levels in PM2.5 across various sites near an industrial zone in Thailand, including areas near main roads, the industrial zone, as well as indoor and outdoor areas of childcare centres. The concentrations of ambient PM2.5 were found to exceed national standards and acceptable limits during the cool dry season, particularly in the industrial zone (46.4 µg/m3), followed by areas near main roads (41.0 µg/m3) and childcare centres (31.6 µg/m3). The impact of the indoor–outdoor relationship on PM2.5 concentration within childcare centres varied. During the cool dry season, Aluminium had the highest concentration, while lead (Pb) across all sites raised environmental concerns. Remarkably, indoor childcare centres showed higher Pb levels than industrial zones and areas near the main road. Principal Component Analysis revealed the distinct factors linked to specific metals, implying contributions from industrial and transportation sources. Lead isotopic analysis indicated potential associations between lead sources and industries like smelting and refining. During the cool dry season, non-carcinogenic risks were concerning (HI > 1), especially near roads and industrial areas. Vulnerabilities were also observed in students and teachers within indoor childcare centres. This study underscores the importance of monitoring and reducing heavy metal pollution in PM2.5, especially in childcare centres near industrial zones, to preserve public health and regional air quality.
Stakeholder Theory, Public Engagement, and Epistemic Injustice: The Case of Covid-19 Vaccine Hesitancy in Scotland’s African, Caribbean, and Black Communities
Authors: Adekola Josephine U. , Chia Robert 
Published: August 2024

AbstractThe adoption of a stakeholder approach to public engagement within the public sector has been extensive. However, there remain critical gaps in the understanding of stakeholder participation arising from hidden disparities that contribute to unequal access to communication channels, information, and hence ultimately knowledge and decision making. The term “epistemic injustice” has been used to describe such inequality of access and consequently, the outcome that ensues. Epistemic injustice is much overlooked in stakeholder theory. This article shows how epistemic injustice can act as a barrier to effective stakeholder engagement and hence to successful public policy formulation and implementation. We use the case of vaccine hesitancy among Scotland’s African, Caribbean, and Black (ACB) communities to illustrate this problem of unequal participation. The study drew on primary data involving 85 participants and secondary data sources from extant literature and explored salient factors shaping barriers to vaccine uptake during the recent pandemic. The findings demonstrate how the failure to grasp epistemic injustice undermines the effectiveness of the stakeholder approach, even with the most well-intentioned efforts. We argue that epistemic injustice is a critical barrier to effective stakeholder approaches.
»Darum gibt es im Grunde keine andre Beredsamkeit als die göttliche«. Die Predigt und die Krise der Rhetorik um 1800 – literaturwissenschaftliche und theologische Perspektiven
Authors: Weidner Daniel , Conrad Ruth 
Published: August 2024

ZusammenfassungDer Beitrag betrachtet die verbreitete Diagnose einer ›Krise der Rhetorik‹ um 1800 aus der bisher weitgehend vernachlässigten Perspektive der Predigt. An vier exemplarischen Fällen wird gezeigt, wie die Rhetorik in der Predigt fortwirkt und sich transformiert. Franz Theremin bekräftigt noch einmal die Funktion der Rhetorik und repräsentiert die weitgehend ungebrochene Kontinuität rhetorischen Wissens in Homiletik und Predigtpraxis des 19. Jahrhunderts. Johann G. Fichte entwickelt das Format einer philosophischen Predigt, die gerade als Propädeutik der an sich antirhetorischen kritischen Philosophie dienen soll. Friedrich D. E. Schleiermacher entwickelt aus dem Problem der Mitteilbarkeit religiösen Wissens eine neue Konzeption der Predigt und auch ein höchst einflussreiches Konzept der Religion. Karl P. Moritz erzählt die Verkündigung kunstreligiöser Überlegungen und stellt im komischen Misslingen dieser Verkündigung gerade die Grenzen dieser Überlegungen aus. In der Zusammenschau der vier Fallstudien lässt sich die ›Krise der Rhetorik‹ differenzierter beschreiben und eine Predigtforschung entwerfen, die literaturwissenschaftliche und theologische Perspektiven verbindet.
The applications and prospects of big data in perioperative anesthetic management
Authors: Zhu Yiziting , Liu Xiang , Li Yujie , Yi Bin 
Published: August 2024

AbstractPerioperative anesthetic management entails a multitude of decision-making processes within complex medical scenarios. These demand the continuous and dynamic execution of precise decisions which poses significant challenges. In the age of big data, the exponential growth in data volume from diverse sources has revolutionized many fields, including healthcare, finance, and marketing. Machine learning has emerged as a powerful tool for analyzing big data, enabling the handling of large datasets and uncovering intricate patterns and relationships. The application of big data and artificial intelligence algorithms is gradually being integrated, enabling effective task completion in various stages of perioperative management, including risk prediction, decision support, and auxiliary examination. Through in-depth analysis of big data, healthcare professionals can gain insights into patient prognoses. This review provides a comprehensive overview of the distinctive features of perioperative big data and its applications in anesthesia management during the perioperative period.