bluuebunny/crossref_metadata_2025_split huggingface dataset:
Augmented histopathology: Enhancing colon cancer detection through deep learning and ensemble techniques
Authors: Gowthamy J , Ramesh S. S. Subashka 
Published: September 2024

AbstractColon cancer poses a significant threat to human life with a high global mortality rate. Early and accurate detection is crucial for improving treatment quality and the survival rate. This paper presents a comprehensive approach to enhance colon cancer detection and classification. The histopathological images are gathered from the CRC‐VAL‐HE‐7K dataset. The images undergo preprocessing to improve quality, followed by augmentation to increase dataset size and enhance model generalization. A deep learning based transformer model is designed for efficient feature extraction and enhancing classification by incorporating a convolutional neural network (CNN). A cross‐transformation model captures long‐range dependencies between regions, and an attention mechanism assigns weights to highlight crucial features. To boost classification accuracy, a Siamese network distinguishes colon cancer tissue classes based on probabilities. Optimization algorithms fine‐tune model parameters, categorizing colon cancer tissues into different classes. The multi‐class classification performance is evaluated in the experimental evaluation, which demonstrates that the proposed model provided highest accuracy rate of 98.84%. In this research article, the proposed method achieved better performance in all analyses by comparing with other existing methods.Research Highlights
Deep learning‐based techniques are proposed.
DL methods are used to enhance colon cancer detection and classification.
CRC‐VAL‐HE‐7K dataset is utilized to enhance image quality.
Hybrid particle swarm optimization (PSO) and dwarf mongoose optimization (DMO) are used.
The deep learning models are tuned by implementing the PSO‐DMO algorithm.
Assessment of the biliary branching pattern of the caudate lobe in perihilar cholangiocarcinoma using ENBD‐CT cholangiography
Authors: Akita Masayuki , Yanagimoto Hiroaki , Tsugawa Daisuke , Sofue Keitaro , Gon Hidetoshi , Komatsu Shohei , Toyama Hirochika , Kido Masahiro , Ajiki Tetsuo , Fukumoto Takumi 
Published: September 2024

AbstractBackgroundPreoperative recognition of the anatomy of caudate biliary branches is important for the safe and complete resection of perihilar cholangiocarcinoma (PHC). In the present study, we identified these branches using an endoscopic nasobiliary drainage tube (ENBD).MethodsBetween January 2012 and October 2022, 89 patients with suspected PHC underwent computed tomographic (CT) cholangiography through ENBD and caudate biliary branching patterns were examined. Multidetector raw CT (MDCT) scans on 85 patients with PHC without biliary drainage were also investigated. The caudate biliary branches detected by each modality were evaluated.ResultsENBD‐CT cholangiography detected 206 caudate branches (2.44 branches/patient), while MDCT identified 62 branches (0.78 branches/patient). ENBD‐CT cholangiography showed that 89 caudate branches drained into the left hepatic duct (LHD), 87 into the posterior hepatic duct (Bpost), and 30 into the right hepatic duct. LHD and Bpost were the common roots of the caudate branches. Some branches (20%) joined the contralateral hepatic duct across the left–right border, but not the anterior hepatic duct or infraportal‐type Bpost.ConclusionsENBD‐CT cholangiography clearly showed the caudate biliary branches in patients with PHC after biliary drainage.
The Study of Reaction of Hexafluoro‐1,4‐Napthoquinone With Substituted 5‐Aminopyrazoles
Authors: Kudryavtseva Ekaterina N. , Lichitsky Boris V. , Komogortsev Andrey N. , Milyutin Constantine V. , Tretyakov Evgeny V. 
Published: September 2024

ABSTRACTFor the first time, the interaction of perfluoro‐1,4‐naphthoquinone with various 5‐aminopyrazoles was investigated. It was shown that three types of products can be obtained depending on the structure of starting aminopyrazole. For all examples, the substitution of one fluorine atom in quinone moiety was observed. Wherein, in most cases, the starting aminopyrazoles act as a C‐nucleophile leading to 2‐(5‐aminopyrazol‐4‐yl)‐3,5,6,7,8‐pentafluoronaphthalene‐1,4‐diones. At the same time substrates unsubstituted at ring nitrogen atom regiospecifically react at aminogroup resulting in the formation of 2,5,6,7,8‐pentafluoro‐3‐((pyrazol‐5‐yl)amino)naphthalene‐1,4‐diones. Besides that, the absence of steric hindrance in the pyrazole unit allowed us to direct the process at nitrogen atom in Position 2 and synthesize zwitter‐ionic 3‐(5‐aminopyrazol‐2‐ium‐2‐yl)‐5,6,7,8‐tetrafluoro‐1,4‐dioxo‐1,4‐dihydronaphthalen‐2‐olates. The structures of two types of obtained products were confirmed by x‐ray analysis.
Exploring the effects of Merkel cell polyomavirus T antigens expression in REH and MCC13 cells by methylome and transcriptome profiling
Authors: Macamo Amanda , Liu Dan , Färber Martina , Borman Felix , van den Oord Joost , Winnepenninckx Véronique , Klufah Faisal , Chteinberg Emil , zur Hausen Axel 
Published: September 2024

AbstractMerkel cell carcinoma (MCC) is a rare, aggressive skin cancer with a tripled incidence in the US and Europe over the past decade. Around 80% of MCC is linked to Merkel cell polyomavirus, but the cell of origin remains unknown. We stably introduced Merkel cell polyomavirus (MCPyV)‐sT) and LT antigens to MCC13 and REH cell lines, analyzing DNA methylation and gene transcriptional regulation. Gene ontology analysis assessed MCPyV effects, and integrative analysis correlated gene expression and methylation. Expression patterns were compared with 15 previously sequenced primary MCCs. We found that MCPyV‐LT induces DNA methylation changes in both cell lines, while MCPyV‐sT only affected REH cells. Greater gene expression changes are observed in MCC13 cells, with upregulated genes associated with cellular components and downregulated genes related to biological processes. Integrative analysis of differentially expressed genes (DEG) and differentially methylated regions (DMR) of REH cell lines revealed that no genes were commonly methylated and differentially expressed. The study compared DEGs and DMG in MCC13 and REH cells to overlapping genes in MCPyV‐positive cell lines (MKL1, MKL2, and WaGa), identifying hypomethylated genes in the gene body and hypermethylated genes at TSS1500. GO analysis of the two cell lines showed that MCPyV‐TAs can downregulate genes in MHC‐I pathways; this downregulation offers a target that can be used to create novel and efficient MCC immunotherapy approaches. Finally, it was confirmed that MCPyV‐LT controls gene expression in MCC tissues using an integrative investigation of DNA methylation and gene expression.
Delay in Time to Adjuvant Chemotherapy and its Impact on Oncological Outcomes in Patients Undergoing Optimal Cytoreductive Surgery for Advanced Ovarian Cancer: Analysis of 1480 Cases From the Indian HIPEC Registry
Authors: SP Somashekhar , C Rohit Kumar , KR Ashwin , Y Ramya , N Arun Kumar , Fernandez Aaron Marian , Ahuja Vijay 
Published: September 2024

ABSTRACTBackground and ObjectivesThe impact of delay in initiation of adjuvant chemotherapy following optimal CRS in different settings of treatment for advanced ovarian cancer needs to be studied with special reference to CRS HIPEC.MethodsThe 1480 advanced EOC patients underwent optimal CRS, followed by adjuvant chemotheraphy, with or without intraperitoneal (IP) chemotherapy in Normothermic or Hyperthermic form. Interval between the day of surgery and start of adjuvant chemotherapy and its impact on outcome was analyzed.ResultsCRS, CRS with IP or HIPEC was done in 400, 480, and 600 patients respectively. Median interval of starting adjuvant chemotherapy was 32 days CRS group, 34 days CRS + IP group and 41 days CRS + HIPEC group. Delay in chemotherapy impacted on recurrence free survival (RFS) in CRS + IV group (36 vs. 17 months: p = 0.02) and some impact in CRS + IP group (38 vs. 28 months; P 0.78) and no impact on CRS + HIPEC group (35 vs. 32 months; p = 0.17).ConclusionsDelay in starting adjuvant chemotherapy adversely affects RFS in patients undergoing optimal CRS alone. However, the delay didn't have an impact in the CRS + HIPEC group. Well‐designed clinical studies are required to evaluate the impact of single dose of HIPEC.
Efficacy of Alexandrite Laser in the Treatment of Pigmented Actinic Keratoses: A Pivotal Study
Authors: Bighetti Stefano , Zane Cristina , Zerbinati Nicola , Arisi Mariachiara , Caravello Simone , Maione Vincenzo , Calzavara‐Pinton Piergiacomo , Bettolini Luca 
Published: September 2024

ABSTRACTObjectivesPigmented actinic keratoses (PAKs), a pigmented variant of actinic keratosis, present diagnostic challenges due to their resemblance to both benign and malignant lesions. Conventional therapies have inconsistent outcomes and may cause undesirable side effects. This study investigates the efficacy of the Alexandrite laser, a pulsed laser with selective melanin absorption, for PAK treatment. Through dermoscopic analysis pretreatment, it aims to identify predictive patterns for better treatment outcomes.Materials and MethodsPatients with PAKs were enrolled in a multicenter study, receiving standardized Alexandrite laser therapy. Detailed dermoscopic evaluations were conducted pretreatment. The Physician's Global Assessment (PGA) and Target Lesion Pigmentation (TLP) scales measured treatment efficacy.ResultsThe study included 50 patients with 60 PAKs. Following treatment, there was a statistically significant reduction in TLP scores, particularly in lesions with pigmented pseudo‐networks and gray‐brownish dots, which were linked to improved outcomes. No adverse effects were reported, suggesting the safety and tolerability of the laser treatment.ConclusionThe Alexandrite laser emerges as a promising modality for the management of PAK pigmentation, with specific dermoscopic patterns being indicative of a favorable response. This study reinforces the critical importance of dermoscopic expertise in the selection and optimization of treatment for PAKs. Future research should focus on comparative studies with different lasers or combination therapies to develop a more comprehensive treatment framework for PAKs.
Investigating the Impact of Pore Size and Specification on Soft Tissue Ingrowth in 3D‐Printed PEEK Material
Authors: Zhang Zibo , Li Zenghuai , Wang Donglai , Feng Jiangang , Feng Qi 
Published: September 2024

AbstractBone pelvis tumor resection and reconstruction is a complex surgical procedure that poses challenges in soft tissue reconstruction despite advancements in stabilizing pelvic structure. This study aims to investigate the potential of using Polyetheretherketone (PEEK) material in repairing and reconstructing soft tissues surrounding pelvic implants. Specifically, the study focuses on exploring the effectiveness of 3D printed porous PEEK material in promoting cell growth and adhesion. The interaction between PEEK materials with different pore sizes (200, 400, 600 µm) and different specifications (through‐hole (T)/non‐through‐hole (C)) is evaluated by cell experiments and animal experiments. The soft tissue ingrowth potential of PEEK materials is evaluated by cell growth and adhesion observation. The findings indicate that PEEK material, particularly the T400 variant, exhibits stronger interaction with muscle tissue compared to its interaction with bone and fibrous tissue. The moderately sized pores present in the T400 material facilitate enhanced cell adhesion and penetration, thereby promoting cell growth and differentiation. PEEK materials with through‐hole structures show promise for applications involving the repair and reconstruction of soft tissues and muscle tissue. The study provides valuable insights into the development and application of biomedical materials, specifically PEEK, contributing to the advancement of pelvic tumor resection and reconstruction techniques.
Optical Surface Roughness Estimation Using Artificial Intelligence
Authors: Maxa Jacob , Nowottnick Mathias 
Published: September 2024

ABSTRACTA system for analysing steel plates is presented for an application in the wind power industry. The objective of the system is to assess the surface roughness as a preliminary step for the application of an anti‐corrosion coating. A number of noncontact sensor systems were considered, with the laser triangulation scanner proving to be the optimal solution. The samples are analysed in a test stand and the roughness is measured with this optical system. At the same time, the surface is recorded with a CMOS camera. An AI model is created from the sensor fusion of both systems, which can classify individual segments of the surface as well or poorly blasted. In the following step, the surface roughness is estimated as the Rz parameter by another AI model. An error of less than 6 μm is achieved.
Multi‐site collaborative forecasting of regional visibility based on spatiotemporal convolutional network
Authors: Tian Wei , Lin Chen , Wu Yunlong , Jin Cheng , Li Xin 
Published: September 2024

AbstractRegional visibility forecasting encounters challenges due to data imbalance, temporal non‐linearity and the consideration of multi‐scale spatial factors. To tackle these challenges, this study introduces a novel approach for collaborative multi‐site visibility forecasting based on spatiotemporal convolutional networks. Firstly, we preprocess the ERA5 reanalysis dataset and ground observation dataset, standardizing the spatiotemporal dimensions. We employ correlation coefficient analysis to select relevant meteorological factors. Subsequently, we create a spatiotemporal convolutional network model (TCN_GCN), which combines the power of temporal convolutional network (TCN) and graph convolutional network (GCN). Additionally, a weighted loss function is incorporated, accounting for the distribution of visibility values. The model is trained with multi‐site data, enabling it to learn spatiotemporal visibility patterns across various sites. This empowers the model to generate multi‐site visibility forecasts, thereby significantly improving regional visibility forecasting accuracy. Using 50 meteorological stations in Fujian Province, China, as a case study, we assess the model's predictions using key metrics such as mean absolute error (MAE), root mean square error (RMSE) and coefficient of determination (R2). The experimental results demonstrate that the inclusion of both temporal and spatial features leads to a substantial enhancement in model prediction performance. The TCN_GCN model outperforms other deep learning methods in multi‐site visibility forecasting, highlighting its effectiveness and superiority in improving regional visibility forecasting accuracy.
High‐resolution CMIP6 analysis highlights emerging climate challenges in alpine and Tibetan Tundra zones
Authors: Fallah Bijan , Rostami Masoud , Didovets Iulii , Dong Zhiwen 
Published: September 2024

AbstractWe employ a high‐resolution Köppen climate classification dataset to examine shifts in Tundra zones within the Alps and Asia. Our analysis shows substantial reductions in Tundra areas by the mid‐21st century under different Shared. Socioeconomic pathways (SSP1‐2.6, SSP3‐7.0, SSP5‐8.5). Tundra zones in the Alps and the Tibetan Plateau are crucial for their unique climates and role as water reservoirs. Characterized by short, mild summers and long, severe winters, these zones are vital for the glaciers and perennial snow. The projected climate instability may significantly reduce alpine snow cover by mid‐century with irreversible consequences. A 2°C temperature increase from the 1981–2010 baseline could eliminate the Tundra climate in the Alps and reduce it by over 70% in Asia. This is particularly concerning given that rivers from the Tibetan Plateau sustain nearly 40% of the global population.
Reconstructing and analyzing the invariances of low‐dose CT image denoising networks
Authors: Eulig Elias , Jäger Fabian , Maier Joscha , Ommer Björn , Kachelrieß Marc 
Published: September 2024

AbstractBackgroundDeep learning‐based methods led to significant advancements in many areas of medical imaging, most of which are concerned with the reduction of artifacts caused by motion, scatter, or noise. However, with most neural networks being black boxes, they remain notoriously difficult to interpret, hindering their clinical implementation. In particular, it has been shown that networks exhibit invariances w.r.t. input features, that is, they learn to ignore certain information in the input data.PurposeTo improve the interpretability of deep learning‐based low‐dose CT image denoising networks.MethodsWe learn a complete data representation of low‐dose input images using a conditional variational autoencoder (cVAE). In this representation, invariances of any given denoising network are then disentangled from the information it is not invariant to using a conditional invertible neural network (cINN). At test time, image‐space invariances are generated by applying the inverse of the cINN and subsequent decoding using the cVAE. We propose two methods to analyze sampled invariances and to find those that correspond to alterations of anatomical structures.ResultsThe proposed method is applied to four popular deep learning‐based low‐dose CT image denoising networks. We find that the networks are not only invariant to noise amplitude and realizations, but also to anatomical structures.ConclusionsThe proposed method is capable of reconstructing and analyzing invariances of deep learning‐based low‐dose CT image denoising networks. This is an important step toward interpreting deep learning‐based methods for medical imaging, which is essential for their clinical implementation.
Highly accelerated non‐contrast‐enhanced time‐resolved 4D MRA using stack‐of‐stars golden‐angle radial acquisition with a self‐calibrated low‐rank subspace reconstruction
Authors: Zhao Tianrui , Tang Jianing , Krumpelman Chase , Moum Sarah J. , Russin Jonathan J. , Ansari Sameer A. , Chen Zhifeng , Feng Li , Yan Lirong 
Published: September 2024

AbstractPurposeTo develop a highly accelerated non‐contrast‐enhanced 4D‐MRA technique by combining stack‐of‐stars golden‐angle radial acquisition with a modified self‐calibrated low‐rank subspace reconstruction.MethodsA low‐rank subspace reconstruction framework was introduced in radial 4D MRA (SUPER 4D MRA) by combining stack‐of‐stars golden‐angle radial acquisition with control‐label k‐space subtraction‐based low‐rank subspace modeling. Radial 4D MRA data were acquired and reconstructed using the proposed technique on 12 healthy volunteers and 1 patient with steno‐occlusive disease. The performance of SUPER 4D MRA was compared with two temporally constrained reconstruction methods (golden‐angle radial sparse parallel [GRASP] and GRASP‐Pro) at different acceleration rates in terms of image quality and delineation of blood dynamics.ResultsSUPER 4D MRA outperformed the other two reconstruction methods, offering superior image quality with a clear background and detailed delineation of cerebrovascular structures as well as great temporal fidelity in blood flow dynamics. SUPER 4D MRA maintained excellent performance even at higher acceleration rates.ConclusionsSUPER 4D MRA is a promising technique for highly accelerating 4D MRA acquisition without comprising both temporal fidelity and image quality.
Custom integration of a magnetic‐field monitoring system into a 32‐channel MRI head coil
Authors: Schmidt Tim , Lee Yoojin , Nagy Zoltan 
Published: September 2024

AbstractPurposeCustomizing a Siemens 32‐channel coil for use in a Philips 3T MRI system with incorporated magnetic field probes for collecting high‐quality MRI and magnetic‐field monitoring data concurrently.MethodsThe development process of the custom coil involved several (iterative) phases. Standard temporal SNR and B1+ data were collected with the 32‐channel Siemens and for reference the 32‐channel/8‐channel Philips head coils before and after the custom coil was made compatible with the 3T Philips Achieva system, and magnetic field probes were installed into it along with ancillary electronics around it. Quality assurance tests were conducted in each of the build phases to ensure that the modifications did not affect MRI or field‐monitoring data negatively. To test the finished custom coil, we collected high angular resolution diffusion imaging (HARDI) datasets on a spherical silicon oil phantom both with and without concurrent field monitoring and a 32‐channel Philips coil without concurrent field monitoring, where the latter two served as reference scans to assess the improved performance of the custom coil with field monitoring. Similar HARDI‐MRI data were also collected in vivo with the finished custom coil together with field monitoring data.ResultsThe custom coil provided excellent temporal SNR especially at the edges where cortical gray matter is expected. When using concurrent field monitoring in HARDI acquisitions, the custom coil alleviated ghosting artifacts in phantom data and provided in vivo images with 1.4‐mm isotropic resolution.ConclusionThe custom MRI coil with integrated magnetic‐field monitoring probes provided improved imaging performance.
Physiotherapists' Treatment Strategies and Delineation of Areas of Responsibility for People With Musculoskeletal Conditions and Comorbidities in Private Physiotherapy Practice: A Qualitative Study
Authors: Lyhnebeck Anna Bernhardt , Risør Mette Bech , Guassora Ann Dorrit , Andersen John Sahl , Skou Søren T. 
Published: September 2024

ABSTRACTBackgroundPatients with multiple chronic conditions, for example, musculoskeletal conditions and comorbidities, often receive inadequate and sometimes even contradictory care. Physiotherapists are well qualified to manage patients with musculoskeletal conditions and comorbidities due to their education and experience with rehabilitation; however, it is unknown which challenges they face when treating these patients.AimTo identify challenges, treatment strategies, and delineations of areas of responsibility among physiotherapists working in private physiotherapy practice when treating people with musculoskeletal conditions and comorbidities.MethodsQualitative study using focus group discussions and participant observations of 13 physiotherapists working in Danish private physiotherapy clinics. Grounded theory was applied to guide the analysis.ResultsTwo major themes emerged from the focus groups and the observations (1) The necessity of adapting management to the patients and their treatment trajectory; (2) The dilemma of overall responsibility for coordinating care. The physiotherapists described different elements of adapting their management, including being challenged on time, taking extra care of the patient, and having to adjust to a fluctuating course of treatment. The dilemma in coordinating care concerned whether the responsibility should lie with the physiotherapist, other healthcare professionals, or the patients, and whether to treat only the condition on the referral or to treat all the conditions the patient had.ConclusionPhysiotherapists use adapted strategies for diagnosing and treating patients with musculoskeletal conditions and comorbidities and are uncertain about the overall responsibility for coordinating care and whether they should focus on the index condition alone or also the other comorbidities the patient has.
Escape the classroom: Wissenschaft interaktiv
Authors: Rubner Isabel , Ditter David , Weiser David , Ditter Rebekka , Lukas Sarah 
Published: September 2024

AbstractIm Projekt Science4Exit sind experimentelle Escape Games digital angereichert. Schüler:innen machen sich so spielerisch mit naturwissenschaftlichen Themen vertraut und stärken dabei Schlüsselkompetenzen. Betreut werden sie von Studierenden, die dadurch Erfahrungen für den Lehrberuf sammeln.
Für Chemie und Pharma formulieren
Authors: Huck Mathias 
Published: September 2024

AbstractSoftware hilft, etwa Medikamente oder Reinigungsmittel zu entwickeln und die Rezepte zu aktualisieren. Ein Beispiel aus der Beschichtungsindustrie zeigt einen Ansatz, der mit künstlicher Intelligenz arbeitet und sich an Unternehmensbedürfnisse anpassen lässt.