bluuebunny/crossref_metadata_2025_split huggingface dataset:
Geschlechtsspezifische Unterschiede in der Adipositaschirurgie: Epidemiologie, Therapie und Ergebnisse
Authors: Téoule Patrick , Pozek Ema , Hielscher Thomas , Reißfelder Christoph , Stier Christine , Otto Mirko , Schölch Sebastian 
Published: August 2024

ZusammenfassungIn dieser Studie werden geschlechtsspezifische Unterschiede bei Adipositas und deren Behandlung mittels metabolisch/bariatrischer Chirurgie (MBS) untersucht. Die Datenbasis umfasst 2393 Patient*innen (1725 Frauen, 668 Männer) aus einem High-volume-Zentrum für bariatrische Chirurgie. Es wurden demographische, perioperative und Nachuntersuchungsdaten retrospektiv analysiert. Männer wiesen einen signifikant höheren Body-Mass-Index (BMI) und häufiger adipositasassoziierte Erkrankungen auf. Frauen stellten trotz der höheren Prävalenz der Adipositas bei Männern 80 % der operierten Patient*innen. Männer hatten im Mittel längere Operationszeiten bei gleichen Komplikationsraten. Postoperativ zeigte sich bei beiden Geschlechtern ein signifikanter Rückgang des Übergewichts, der bei Frauen etwas stärker ausgeprägt war. Die Studie unterstreicht insbesondere die Notwendigkeit, Männer besser zur Adipositasbehandlung zu motivieren, um gesundheitliche Folgen in dieser Bevölkerungsgruppe zu reduzieren.
Obstacle negotiation in female desert locust oviposition digging
Authors: Klechevski Chen , Kats Lazar , Ayali Amir 
Published: August 2024

AbstractThe female locust lays its eggs deep within soft substrate to protect them from predators and provide optimal conditions for successful development and hatching. During oviposition digging, the female’s abdomen is pooled and extends into the ground, guided by a dedicated excavation mechanism at its tip, comprising two pairs of specialized digging valves. Little is known about how these active valves negotiate the various obstacles encountered on their path. In this study, female locusts oviposited their eggs in specialized sand-filled tubes with pre-inserted 3D-printed plastic obstacles. The subterranean route taken by the abdomen and digging valves upon encountering the obstacles was investigated, characterized, and compared to that in control tubes without obstacles. Data were obtained by way of visual inspection, by utilizing cone beam computed tomography scans in high-definition mode, and by making paraffin casts of the oviposition burrows (after egg hatching). We demonstrate, for the first time, the subterranean navigation ability of the female locust’s excavation mechanism and its ability to circumvent obstacles during oviposition. Finally, we discuss the role of active sensory-motor mechanisms versus the passive embodied function of the valves, central control, and decision-making.
Diabetes technology in people with diabetes and advanced chronic kidney disease
Authors: Galindo Rodolfo J. , Soliman Diana , Cherñavvsky Daniel , Rhee Connie M. 
Published: August 2024

AbstractDiabetes is the leading cause and a common comorbidity of advanced chronic kidney disease. Glycaemic management in this population is challenging and characterised by frequent excursions of hypoglycaemia and hyperglycaemia. Current glucose monitoring tools, such as HbA1c, fructosamine and glycated albumin, have biases in this population and provide information only on mean glucose exposure. Revolutionary developments in glucose sensing and insulin delivery technology have occurred in the last decade. Newer factory-calibrated continuous glucose monitors provide real-time glucose data, with predictive alarms, allowing improved assessment of glucose excursions and preventive measures, particularly during and between dialysis sessions. Furthermore, integration of continuous glucose monitors and their predictive alerts with automated insulin delivery systems enables insulin administration to be decreased or stopped proactively, leading to improved glycaemic management and diminishing glycaemic fluctuations. While awaiting regulatory approval, emerging studies, expert real-world experience and clinical guidelines support the use of diabetes technology devices in people with diabetes and advanced chronic kidney disease.
Graphical Abstract
Do we need a re-TUR after en bloc resection of T1 stage bladder cancer?
Authors: Levy Stephan , Péricart Sarah , Bajeot Anne Sophie , Fakhfakh Sami , Lesourd Marine , Soulié Michel , Pignot Géraldine , Roumiguié Mathieu 
Published: August 2024

Abstract
Background
A second look trans-urethral resection of the bladder (re-TUR) is recommended after the diagnosis of T1 high grade (T1HG) bladder cancer. Few studies have evaluated the results of re-TUR after a first en bloc resection (EBR) and none of them have specifically reported the pathological results on the field of previous T1 disease.

Objective
To report the rate of upstaging and the rate of residual disease (RD) on the field of T1HG lesions resected with EBR.

Materials and methods
Between 01/2014 and 06/2022, patients from 2 centers who had a re-TUR after an EBR for T1HG urothelial carcinoma were retrospectively included. Primary endpoint was the rate of RD including the rate of upstaging to T2 disease on the scar of the primary resection. Secondary endpoints were the rate of any residual disease outside the field.

Results
Seventy-five patients were included. No muscle invasive bladder cancer lesions were found after re-TUR. Among the 16 patients who had a RD, 4 were on the resection scar. All of these lesions were papillary and high grade. RD outside the field of the first EBR was observed in 12 patients.

Conclusion
After EBR of T1HG disease, none of our patients had an upstaging to MIBC. However, the rate of RD either on and outside the field of the EBR remains quite significant. We suggested that predictive factors of residual papillary disease (number of tumors at the initial TUR and concomitant CIS) might be suitable to select patient who will benefit of the re-TUR.
Performance on curriculum-based mathematics assessments in developmental dyscalculia: the effect of content domain and question format
Authors: Roulstone Alison , Morsanyi Kinga , Bahnmueller Julia 
Published: August 2024

AbstractDevelopmental Dyscalculia (DD) is characterised by persistent difficulties in learning mathematical skills, which usually becomes apparent in the early years of schooling. Traditionally, DD is known to affect children’s arithmetic processing, whilst other domains of mathematics receive much less research attention. Nevertheless, contemporary diagnostic guidelines suggest that DD is linked to widespread and diverse difficulties, both within and outside of the domain of numbers. This study examined the performance (i.e., accuracy and number of questions attempted) of children on a curriculum-based mathematics assessment, considering the effect of content domains, question format (i.e., multiple-choice questions vs. constructed response questions) and test half. Participants were forty children aged 8 to 11 years old with DD (n = 20) and a carefully matched control group of typically developing children (n = 20) from primary schools in Northern Ireland. Results revealed that the DD group achieved significantly lower scores than the control group across all areas of the curriculum, and the magnitude of group differences was similar across all content domains. These findings indicate that performance in content domains other than in arithmetic may be equally informative in supporting the identification of children with DD. In addition, we found that using multiple-choice questions may support learners with DD in achieving the best outcome, and, thus, could be useful for assessing mathematics skills in dyscalculic children in classroom contexts. Nevertheless, constructed response questions may show the greatest sensitivity to identifying learners at risk, and could be the most useful in diagnostic settings.
The spectrum of co-existing disease in children with established kidney failure using registry and linked electronic health record data
Authors: Plumb Lucy , Steenkamp Retha , Hamilton Alexander J. , Maxwell Heather , Inward Carol D. , Marks Stephen D. , Nitsch Dorothea 
Published: August 2024

Abstract
Background
Children with established kidney failure may have additional medical conditions influencing kidney care and outcomes. This cross-sectional study aimed to examine the prevalence of co-existing diseases captured in the electronic hospital record compared to UK Renal Registry (UKRR) data and differences in coding.

Methods
The study population comprised children aged < 18 years receiving kidney replacement therapy (KRT) in England and Wales on 31/12/2016. Comorbidity data at KRT start was examined in the hospital record and compared to UKRR data. Agreement was assessed by the kappa statistic. Associations between patient and clinical factors and likelihood of coding were examined using multivariable logistic regression.

Results
A total of 869 children (62.5% male) had data linkage for inclusion. UKRR records generally reported a higher prevalence of co-existing disease than electronic health records; congenital, non-kidney disease was most commonly reported across both datasets. The highest sensitivity in the hospital record was seen for congenital heart disease (odds ratio (OR) 0.65, 95% confidence interval (CI) 0.51, 0.78) and malignancy (OR 0.63, 95% CI 0.41, 0.85). At best, moderate agreement (kappa ≥ 0.41) was seen between the datasets. Factors associated with higher odds of coding in hospital records included age, while kidney disease and a higher number of comorbidities were associated with lower odds of coding.

Conclusions
Health records generally under-reported co-existing disease compared to registry data with fair-moderate agreement between datasets. Electronic health records offer a non-selective overview of co-existing disease facilitating audit and research, but registry processes are still required to capture paediatric-specific variables pertinent to kidney disease.

Graphical Abstract
Comparison of predictive models in postoperative nausea and vomiting in patients undergoing breast cancer surgery
Authors: Maraş Gülseren , Kalaycı Halil , Ceyhan Özlem 
Published: August 2024

Abstract
Background
Post-operative nausea and vomiting remain an unresolved concern in Türkiye and some parts of the world, impacting the quality of the patient's recovery process and diminishing overall satisfaction.

Objective
This study was conducted as a descriptive investigation to compare the incidence of nausea and vomiting following breast cancer surgery with the nausea and vomiting risk scores proposed by Apfel and Koivuranta.

Methods
This study was conducted with 100 patients admitted to the General Surgery service of a university hospital between 31 August 2019 and 31 May 2021 for breast cancer surgery. The patient information form developed by the researchers, Apfel Nausea and Vomiting Risk Score, and Koivuranta Nausea and Vomiting Risk Score were used as data collection tools.

Results
It was identified that 61% of the patients experienced nausea and vomiting within the initial 24 h following surgery. A significant correlation was found between age, post-operative opioid use, motion sickness or history of PONV, and nausea and vomiting (p < 0,05). The sensitivity of the Apfel score obtained was 80%, the specificity was 46%, and the AUC value was 0.686. The sensitivity of the Koivuranta score was 80%, the specificity was 35%, and the AUC value was 0.675 (p < 0.05).

Conclusion
It has been observed that patients experience high rates of nausea and vomiting after breast cancer surgery and that the Apfel and Koivuranta Risk Scores are equally applicable in predicting post-operative nausea and vomiting.
Deepfake detection using convolutional vision transformers and convolutional neural networks
Authors: Soudy Ahmed Hatem , Sayed Omnia , Tag-Elser Hala , Ragab Rewaa , Mohsen Sohaila , Mostafa Tarek , Abohany Amr A. , Slim Salwa O. 
Published: August 2024

AbstractDeepfake technology has rapidly advanced in recent years, creating highly realistic fake videos that can be difficult to distinguish from real ones. The rise of social media platforms and online forums has exacerbated the challenges of detecting misinformation and malicious content. This study leverages many papers on artificial intelligence techniques to address deepfake detection. This research proposes a deep learning (DL)-based method for detecting deepfakes. The system comprises three components: preprocessing, detection, and prediction. Preprocessing includes frame extraction, face detection, alignment, and feature cropping. Convolutional neural networks (CNNs) are employed in the eye and nose feature detection phase. A CNN combined with a vision transformer is also used for face detection. The prediction component employs a majority voting approach, merging results from the three models applied to different features, leading to three individual predictions. The model is trained on various face images using FaceForensics++ and DFDC datasets. Multiple performance metrics, including accuracy, precision, F1, and recall, are used to assess the proposed model’s performance. The experimental results indicate the potential and strengths of the proposed CNN that achieved enhanced performance with an accuracy of 97%, while the CViT-based model achieved 85% using the FaceForences++ dataset and demonstrated significant improvements in deepfake detection compared to recent studies, affirming the potential of the suggested framework for detecting deepfakes on social media. This study contributes to a broader understanding of CNN-based DL methods for deepfake detection.
A lightweight deep learning architecture for malaria parasite-type classification and life cycle stage detection
Authors: Chaudhry Hafiza Ayesha Hoor , Farid Muhammad Shahid , Fiandrotti Attilio , Grangetto Marco 
Published: August 2024

AbstractMalaria is an endemic in various tropical countries. The gold standard for disease detection is to examine the blood smears of patients by an expert medical professional to detect malaria parasite called Plasmodium. In the rural areas of underdeveloped countries, with limited infrastructure, a scarcity of healthcare professionals, an absence of sufficient computing devices, and a lack of widespread internet access, this task becomes more challenging. A severe case of malaria can be fatal within one week, so the correct detection of the malaria parasite and its life cycle stage is crucial in treating the disease correctly. Though computer vision-based malaria detection has been adequately explored lately, the malaria life cycle stage classification is still a relatively unexplored field. In this paper, we introduce a fast and robust deep learning methodology to not only classify the malaria parasite-type detection but also the life cycle stage identification of the infected cell. The proposed deep learning architecture is more than twenty times lighter than the widely used DenseNet and has less than 0.4 million parameters, making it a good candidate to be used in the mobile applications of such economically challenged states for malaria detection. We have used four different publicly available malaria datasets to test the proposed architecture and gained significantly better results than the current state of the art on malaria parasite-type and malaria life cycle classification.
Molecular and morphological support for transferring the tropical African species of Gnidia to Lasiosiphon (Thymelaeaceae: Thymelaeoideae) and a worldwide synopsis of the species
Authors: Olaniyan Oluwayemisi D. , Boatwright J. Stephen , Magee Anthony R. , Manning John C. , van der Bank Michelle 
Published: August 2024

AbstractLasiosiphon Fresen. (Thymelaeaceae: Thymelaeoideae) is now understood to be a morphologically diverse genus distributed across southern and tropical Africa, Madagascar, and India. It is diagnosed morphologically by ± involucrate, mostly pedunculate heads of pentamerous or tetramerous flowers, with or without petaloid scales, and a bright yellow, orange, or red corolla. The taxonomic history of Lasiosiphon has been marked by several revisions in its circumscription and status, particularly regarding its relationship with Gnidia L. Our phylogenetic analysis of nuclear (ITS) and plastid (matK, rbcL, rps16 and trnL-F) regions of an expanded sampling of the tropical African species of Gnidia provides compelling supporting evidence for existing morphological evidence to include all the tropical African species of Gnidia in Lasiosiphon. We accordingly provide 31 new combinations in Lasiosiphon for species of Gnidia that currently lack combinations in that genus. We also provide a comprehensive nomenclator of all currently recognized Lasiosiphon species at the regional level encompassing their distribution across different geographic regions globally. This will serve as the framework for future taxonomic revisions in the genus.
Modified data classification for extreme values in Şen’s innovative trend analysis: A comparative trend study for the Aegean and Eastern Anatolia Regions of Türkiye
Authors: Asikoglu Omer Levend , Alp Harun , Temel Ibrahim 
Published: August 2024

AbstractThe increase in greenhouse gases in the atmosphere has worsened global warming, and marked changes have been observed in meteorological and climatic events, especially since the early 2000s. Trend analysis studies are important for determining changes in meteorological and climatic events over time. This study investigated the trends of maximum precipitation and minimum temperature in the Aegean Region and Eastern Anatolia Region of Türkiye by conducting an innovative trend analysis (ITA), the Mann–Kendall (MK) test, and linear regression analysis (LRA). As a method, ITA has been used together with traditional methods in the last decade, and its advantages have been demonstrated in comparative trend studies. An important contribution of ITA is that it can categorize datasets according to their size (low, medium, and high). The classification technique of the ITA method includes dividing the sorted dataset into three equal parts and separately examining the trends of low, medium, and high data values. This approach is reasonable for datasets with low skewness (or normally distributed series). However, the normal distribution acceptance of ITA data classification is insufficient for trend analysis of data series with extreme values. Therefore, we propose a modified data classification method to rationally examine skewed datasets with the use of quartiles. Our study was performed for the trend analysis of maximum rainfall and minimum temperature data in two regions located in the west and east of Türkiye showing different climatic characteristics. In the first part of the study in which the numerical trend analysis of ITA was evaluated, the MK and LRA methods showed similar results, whereas the ITA detected trends at a greater number of stations owing to its sensitivity feature in detecting trends. In the second part, which included data classification in trend analysis, the equal split data classification used in the ITA and the modified data classification proposed in the study were compared. The comparative results of the trend analysis of the maximum rainfall and minimum temperature data showed the superiority of the proposed data classification in examining the trend of extreme values, especially for maximum rainfall data with relatively high skewness.
A radial basis function method for noisy global optimisation
Authors: Banholzer Dirk , Fliege Jörg , Werner Ralf 
Published: August 2024

AbstractWe present a novel response surface method for global optimisation of an expensive and noisy (black-box) objective function, where error bounds on the deviation of the observed noisy function values from their true counterparts are available. The method is based on Gutmann’s well-established RBF method for minimising an expensive and deterministic objective function, which has become popular both from a theoretical and practical perspective. To construct suitable radial basis function approximants to the objective function and to determine new sample points for successive evaluation of the expensive noisy objective, the method uses a regularised least-squares criterion. In particular, new points are defined by means of a target value, analogous to the original RBF method. We provide essential convergence results, and provide a numerical illustration of the method by means of a simple test problem.
Effect of immunogenetics polymorphism and expression on direct-acting antiviral drug response in chronic hepatitis C
Authors: Abdelaziz Aya Ismail , Abdelsameea Eman , Abdel-Samiee Mohamed , Ghanem Samar E. , Wahdan Sara A. , Elsherbiny Doaa A. , Zakaria Zeinab , Azab Samar S. 
Published: August 2024

Abstract
The prevalence of HCV infection in Egypt has decreased following the introduction of direct-acting antiviral therapy. However, treatment response is influenced by various factors, particularly host immunogenetics such as IL-28B and FOXP3 polymorphisms. The current study examined the impact of SNPs in the FOXP3 gene promoter region on HCV-infected Egyptian patients, along with SNPs in the IL28B gene.This study involved 99 HCV patients who achieved SVR12 after a 12 week DAA treatment while 63 HCV patients experienced treatment failure. IL28B rs12979860 SNP was identified using real-time PCR, while IL28B rs8099917, FOXP3 rs3761548, and rs2232365 SNPs were analyzed using RFLP-PCR. Serum levels of IL28B and FOXP3 were quantified using ELISA technique in representative samples from both groups. The IL28B rs12979860 T > C (P = 0.013) and FOXP3 rs2232365 A > G polymorphisms (P = 0.008) were found to significantly increase the risk of non-response. Responders had higher IL28B serum levels (P = 0.046) and lower FOXP3 levels (P < 0.001) compared to non-responders. Regression analysis showed an association between IL28B rs12979860 and FOXP3 rs2232365 with treatment response, independent of age and gender. A predictive model was developed with 76.2% sensitivity and 91.9% specificity for estimating DAAs response in HCV patients.Our findings confirmed the IL28B rs12979860 T > C and FOXP3 rs2232365 A > G polymorphisms significantly affect DAA treatment response in HCV Egyptian patients. Lower levels of IL-28B along with higher levels of FOXP3 are linked to poor response. Our results may lead to new insights into DAA responsiveness contributing to personalized medicine and improving therapeutic decision-making for HCV patients.

Graphical abstract
The impact of cultural differences on the success of elite labor migration—Evidence from professional soccer
Authors: Bosker Joost , Gürtler Marc 
Published: August 2024

AbstractThe literature finds that cultural differences have a negative impact on the success of international labor migration. However, modeling cultural effects requires a variety of individual-level, firm-level and country-level data that are not sufficiently considered in the literature. Precisely, previous migration experiences are not taken into account and the culture effect is not isolated from adaptation effects that occur with any change of employer. We find that an identified culture effect is biased if such data are not considered. To take these aspects into account, we utilize soccer data with its abundance of single player information and leverage the approaches established in Operations Research to model soccer player performance. To this end, we extend a prominent mixed-effects model to fit the case of international migration and find contrary results compared to the literature: cultural differences positively affect employee value in the long term and we identify a distinct and positive culture effect in the short run for switches between industry-leading firms. Finally, we show that our results are not driven by peculiarities of soccer player data by using a reduced model without isolating general adaptation difficulties from cultural differences. In this (too) simple model, in accordance with the literature, the biased negative culture effect emerges.