bluuebunny/crossref_metadata_2025_split huggingface dataset:
Primary squamous cell carcinoma of the kidney with hepatic invasion : a case report
Authors: Takanashi Masato , Asaoka Miho , Imano Masashi , Fujioka Azumi , Oishi Yuka , Matsuda Goro , Chiba Sawako , Hirai Kotaro 
Published: June 2023

Abstract
Background
Primary squamous cell carcinoma of the kidney is very rare, with only eight cases reported to date. We describe herein what we believe is the first case of hepatic invasion of a primary squamous cell carcinoma that originated in the kidney.
Case Presentation
A 73-year-old asymptomatic man was referred to our hospital for further evaluation after an abdominal ultrasonography revealed a right renal mass. Contrast-enhanced computed tomography (CT) showed a hypodense mass with capsular enhancement from the upper pole of the right kidney to the right lobe of the liver.
Ultrasonography-guided renal biopsy was performed to identify the origin of tumor. The pathology indicated a squamous cell carcinoma, but it was unclear whether it was a primary carcinoma of the kidney or a metastatic growth derived from other organs.
Chronic fever appeared and the patient’s general malaise worsened day by day. Contrast-enhanced CT one month after the previous one showed rapid growth of the right renal tumor and progressive hepatic invasion.
Radical nephrectomy and hepatic resection of the posterior segment by laparotomy was performed. Pathological analysis indicated the origin of this tumor was tubular epithelium, and the patient was diagnosed with primary squamous cell carcinoma of the kidney, pT4.
Conclusions
This case showed that squamous cell carcinoma of the kidney can invade the liver, and this cancer can progress very rapidly, on a daily basis.
When hepatic invasion of renal squamous cell carcinoma is suggested, combined renal-hepatic resection should be considered. In addition, once this disease is suspected, surgery must be performed as soon as possible, considering the speed of its progression.
Unveiling metabolic pathways involved in the extreme desiccation tolerance of an Atacama cyanobacterium
Authors: Moore Rachel A. , Azua-Bustos Armando , González-Silva Carlos , Carr Christopher E. 
Published: June 2023

AbstractGloeocapsopsis dulcisstrain AAB1 is an extremely xerotolerant cyanobacterium isolated from the Atacama Desert (i.e., the driest and oldest desert on Earth) that holds astrobiological significance due to its surprising ability to biosynthesize compatible solutes at ultra-low water activities. We sequenced and assembled theG. dulcisgenome de novo using a combination of long- and short-read sequencing, which resulted in high-quality consensus sequences of the chromosome and two plasmids. We leveraged theG. dulcisgenome to generate a genome-scale metabolic model (iGd895) to simulate growthin silico. iGd895represents, to our knowledge, the first genome-scale metabolic reconstruction developed for an extremely xerotolerant cyanobacterium. The model's predictive capability was assessed by comparing thein silicogrowth rate within vitrogrowth rates ofG. dulcis, in addition to the synthesis of trehalose.iGd895allowed us to explore key metabolic processes such as essential pathways for water-stress tolerance, and significant alterations to reaction flux distribution and metabolic network reorganization resulting from water limitation. Our study provides insights into the potential metabolic strategies employed byG. dulcis, emphasizing the crucial roles of compatible solutes, metabolic water, energy conservation, and the precise regulation of reaction rates in their adaptation to water stress.
Comparison between intravoxel incoherent motion and splenic volumetry to predict liver fibrosis in preoperative patients
Authors: Arakane Takayuki , Okada Masahiro , Nakazawa Yujiro , Tago Kenichiro , Yoshikawa Hiroki , Mizuno Mariko , Abe Hayato , Higaki Tokio , Okamura Yukiyasu , Takayama Tadatoshi 
Published: June 2023

Abstract
Background
Hepatic fibrosis (HF) is an important factor in patients for liver surgery, because HF may lead to surgical restrictions and affect the patient's prognosis. Intravoxel incoherent motion (IVIM) is used for HF investigation, and the restricted diffusion observed in patients with cirrhosis may be related to D* variations. Splenic volumetry (SV) has been reported to be effective in the evaluation of severe cirrhosis. Our purpose of this study is to compare the predictive ability of IVIM and SV for HF.
Methods
This study included 67 patients with pathologically staged HF who underwent magnetic resonance imaging and computed tomography (CT). SV was semi-automatically measured from the CT images. IVIM indices, such as the slow diffusion coefficient related to molecular diffusion (D), fast diffusion coefficient related to perfusion in microvessels (D*), apparent diffusion coefficient (ADC), and perfusion-related diffusion fraction (f), were calculated with 10 b-values by two observers (R1 and R2). Receiver operating characteristic curve analysis was performed to determine the predictive ability of HF for IVIM and SV/body surface area (BSA). The inter-rater agreement was discussed for each IVIM parameter.
Results
D (P = 0.718 for R1, P = 0.087 for R2) and D* (P = 0.513, P = 0.708, respectively) showed a poor correlation with HF grade. ADC (P = 0.034 and P = 0.528, respectively) and f (P < 0.001 and P = 0.007, respectively) decreased as HF progressed, whereas SV/BSA increased (P = 0.015 for R1). The AUCs of SV/BSA (0.649–0.698 for R1) were higher than those of f (0.575–0.683 for R1 + R2) for severe HF (≥ F3-4 and ≥ F4), although the AUCs of f (0.705–0.790 for R1 + R2) were higher than those of SV/BSA (0.628 for R1) for mild or no HF (≤ F0-1). However, no significant differences in the ability to identify HF were observed between IVIM and SV/BSA.
Conclusions
SV/BSA allows a higher estimation for evaluating severe HF than IVIM. IVIM is more suitable than SV/BSA for the assessment of mild or no HF.
Mapping global zoonotic niche and interregional transmission risk of monkeypox: a retrospective observational study
Authors: Sun Yan-Qun , Chen Jin-Jin , Liu Mei-Chen , Zhang Yuan-Yuan , Wang Tao , Che Tian-Le , Li Ting-Ting , Liu Yan-Ning , Teng Ai-Ying , Wu Bing-Zheng , Hong Xue-Geng , Xu Qiang , Lv Chen-Long , Jiang Bao-Gui , Liu Wei , Fang Liqun 
Published: June 2023

Abstract
Background: The outbreaks of monkeypox have been ongoing in non-endemic countries since May 2022. A thorough assessment of its global zoonotic niche and potential transmission risk is lacking.
Methods: We established an integrated database on global monkeypox virus (MPXV) occurrence during 1958−2022. Phylogenetic analysis was performed to examine the evolution of MPXV and effective reproductive number (Rt) was estimated over time to examine the dynamic of MPXV transmissibility. Potential ecological drivers of zoonotic transmission and interregional transmission risk of MPXV were examined.
Results: A total of 49 432 human patients and 20 kinds of animals with MPXV infections were reported in 78 countries as of July 24, 2022. Based on 525 whole genome sequences, two main clades of MPXV were formed, of which Congo Basin clade has a higher transmissibility than West African clade before the 2022-monkeypox, estimated by the overall Rt (0.81 vs. 0.56), and the latter significantly increased in the recent decade. Rt of 2022-monkeypox varied from 1.14 to 4.24 among the 15 continuously epidemic countries outside Africa, with the top three as Peru (4.24, 95% CI: 2.89–6.71), Brazil (3.45, 95% CI: 1.62–7.00) and the United States (2.44, 95% CI: 1.62–3.60). The zoonotic niche of MPXV was associated with distributions of Graphiurus lorraineus and Graphiurus crassicaudatus, richness of Rodentia, and four ecoclimatic indicators. Besides endemic areas of Africa, more areas of South America, the Caribbean States, and Southeast and South Asia are ecology-suitable for MPXV occurrence once the virus invades. The majority of Western Europe have high-imported risk of monkeypox from Western Africa, whereas France and the United Kingdom have potential-imported risk of Congo Basin clade MPXV from Central Africa. Among the top 15 countries with high MPXV-imported risk from main countries of 2022-monkeypox outbreaks, eleven of them were located at Europe with the highest risk in Italy, Ireland and Poland.
Conclusions: The suitable ecological niche of MPXV is not limited to Africa, and the transmissibility of MPXV during the 2022-monkeypox outbreaks significantly increases. European have higher imported risk both from endemic areas and current epidemic countries. Future surveillance and targeted intervention programs are needed in its high-risk regions informed by updated prediction.
Physicochemical, Functional and Morphological Properties of Gamma- irradiated Cassava Starch
Authors: Verma Ruchi , Chauhan Neelash , Chandra Suresh 
Published: June 2023

Abstract
The purpose of the study was to investigate the physicochemical, functional and morphological properties of untreated and irradiated treated starches. Starch isolated from cassava which was exposed to gamma-irradiation at different doses 5, 7.5 and 10 kGy. Irradiation decreased the moisture, fat, pH, content and increased the protein, fibre and Ash content. The result revealed that the moisture content of the cassava starch ranges of 9.52 therefore the bulk and tapped density was decreased ranged from 0.421 g/cc and 0.710 g/cc, respectively. Moisture content affects the flow properties of the starch. Swelling, solubility index, oil absorption capacity and water absorption capacity increased significantly with dose, while as syneresis decreased with dose. The Carr’s Index and Hausner ratio was high as the standard values therefore according to the result the flowability of the cassava flour was poor. Scanning electron microscopy (SEM) revealed regular, oval, polyhedral shape starch granules and slightly shrinkage of the granules, no fissures were seen after irradiation.
Robinobiosylation of tyrosol by seed meal from Rhamnus cathartica.
Authors: Haluz Peter , Mastihubová Mária , Potocká Elena Karnišová , Pančík Filip , Mastihuba Vladimir 
Published: June 2023

Abstract
Tyrosol robinobioside was prepared under catalysis of robinobiosidase-containing seed meal from common buckthorn Rhamnus cathartica. Robinin, a flavonoid isolated from the flowers of black locust (Robinia pseudoacacia) served as the donor of robinobiose. The glycosylation proceeded predominantly on the primary hydroxyl of tyrosol, typically yielding mixtures of isomeric glycosides in ratios of 5:1 to 8:1 with overall yields of robinobiosides higher than 20%. This is the first robinobiosylation promoted under enzymatic catalysis.
An analysis to enhance the machining performance of micro-EDM for drilling of blind micro-hole using ANN
Authors: Pratap Suresh , Upadhyay Ananya , Sharma Vinay , Datta Somak , Badar M. Affan 
Published: June 2023

Abstract
The high demand for compact and multitasking devices in the market has been a driving force behind the growing interest in microfabrication techniques. These techniques have wide-ranging applications in many industries, including aerospace, automobile, electronics, and defense. Micro electrical discharge machining (µEDM) techniques have the unique ability to produce highly precise and intricate features on small components, which has further fueled the demand for such products. However, with the increasing demand for micro-featured products, there is a pressing need to enhance the process capability of µEDM process. This work aims to address this need by focusing on enhancing the performance of µEDM by varied process parameters and materials such as copper, brass, and tungsten carbide for the drilling of blind micro holes. Surface roughness (SR) and material removal rate (MRR) are the main performance factors taken into account in this investigation. Notably, the minimum SR was achieved on tungsten carbide, while the maximum MRR was achieved using copper electrodes. For SR and MRR, artificial neural network (ANN) models have been constructed that predict with more than 90% accuracy. These findings have significant implications for the future of microfabrication using µEDM.
The FLY-project: Study Protocol for Mixed Methods Research to Explore the Complex Social Dynamics of Sustainable Food-related Lifestyles in Youth in Practical Education
Authors: Etten Soraya van , Jansen Lonneke , Bal Michèlle , Dermody Brian J. , Müller Eggo , de Wit John , Stok Marijn 
Published: June 2023

Abstract
Background
The present-day food system is a key driver of climate change and biodiversity loss, making it imperative for populations to shift towards more sustainable diets. The involvement of youth in this transition is vital because they are in a formative period where their identities, values, and norms, including their food behaviours, are being shaped. Special attention should be paid to youth in practical education because they are often overlooked in existing studies, yet evidence suggests they may lack the necessary resources to support dietary changes, resulting in lower levels of pro-environmental food-related behaviours. The aim of the FLY (Food-related Lifestyles in Youth) project is to study how sustainable food-related lifestyles and underlying factors develop in early adolescence, particularly in Dutch youth in practical education, how these spread in social networks, and to develop community-level intervention strategies to support youths’ transition to sustainable food-related behaviours.
Methods/design
The FLY-project adopts a mixed-method approach. First, two literature reviews are conducted. A systematic review assesses how capabilities, opportunities and motivation are associated with sustainable food behaviours in youth, and how these elements interrelate in determining sustainable food-related lifestyles. A scoping review studies community-level interventions that target sustainable and healthy food-related behaviours. Second, focus groups are conducted to explore the barriers and facilitating factors concerning capabilities, opportunities, and motivations that Dutch youth in practical-level education experience to transition to more sustainable food-related lifestyles. Third, a cohort survey study is conducted to track the dynamic interplay between capabilities, opportunities, motivation, and changes in specific sustainable food behaviours over time, and to assess the diffusion of sustainable food-related lifestyles via social (media) networks. Fourth, an experimental research programme tests promising intervention approaches, some of which are co-created with youth, targeting relevant underlying factors.
Discussion
This paper describes the rationale, conceptual framework, design and methods of the FLY-project. The FLY-project contributes to an understanding of underlying factors of sustainable food-related behaviours in adolescence and results in a multi-component intervention toolkit, with a particular focus on youth in practical education programmes.
GPU-based and Streaming-enabled Implementation of Pre-processing Flow towards Enhancing Optical Character Recognition Accuracy and Efficiency
Authors: Gener Serhan , Dattilo Parker , Gajaria Dhruv , Fusco Alexander , Akoglu Ali 
Published: June 2023

Abstract
Research has demonstrated that digital images can be pre-processed through operations such as scaling, rotation, and blurring to enhance the accuracy of optical character recognition (OCR) by emphasizing important features within the image. Our study employed the open-source Tesseract OCR and found that accuracy can be improved through pre-processing techniques including thresholding, rotation, rescaling, erosion, dilation, and noise removal, based on a dataset of 560 phone screen images. However, our CPU-based implementation of this process resulted in an average latency of 48.32 ms per image, which can hinder the processing of millions of images using OCR. To address this challenge, we parallelized the pre-processing flow on the Nvidia P100 GPU and executed it through a streaming approach, which reduced the latency to 0.825 ms and achieved a speedup factor of 58.6x compared to the serial execution. This implementation enables the use of a GPU-based OCR engine to handle multiple sources of data streams with large-scale workloads.
Retinal and choroidal alterations in migraine patients compared to normal healthy controls
Authors: Conway Miriam L , Ctori Irene 
Published: June 2023

Abstract
Purpose: Migraine is an incapacitating neurovascular disorder which primarily affects the working age population. Researchers have postulated that the transient vascular alterations during each migraine attack, leads to ischemic damage in the eye which can be measured via optical coherence tomography.
Methods: We recruited 29 volunteers: 13 migraineurs (mean age 28±8.8 years; 12 female and 1 male) and 16 age-matched controls (mean age 26.6±6.9; 9 female and 7 male). All individuals underwent a detailed ophthalmic examination by a qualified optometrist and a Migraine Disability Assessment. The investigators were blind to the migraine diagnosis. Retinal Nerve Fibre Layer (RNFL) thickness, Retinal Thickness (RT), Ganglion Cell Complex (GCL), ranging from the inner-limiting membrane to the inner plexiform layer, and Choroidal Thickness (CT) were measured using the 3D OCT-1Maestro, Topcon, a Spectral Domain OCT (SD-OCT) device.
Results: In the migraine population average RNFL was lower for several parameters however, results did not reach statistical significance. A significant decrease in the right eye inferior parafoveal ganglion cell layer in the migraine group of patients (mean = 25.15, SD = 4.08) compared to normal healthy controls (mean = 28.81, SD = 4.85; t = (27) = 2.17, p = 0.039) was documented. No other ganglion cell layer or choroidal thickness reached significance. No significant relationship between ocular thickness parameters and MIDAS score, migraine duration or aura diagnosis was found.
Conclusion: A significant decreasein the right inferior parafoveal ganglion cell layer for migraine patients was reported. All other parameters did not reach significance.
The OCDA-Net: a 3D convolutional neural network-based system for classification and staging of ovarian cancer patients using FDG PET/CT examinations
Authors: Sadeghi Mohammad Hossein , sina sedigheh , Alavi Mehrosadat , Giammarile Francesco 
Published: June 2023

Abstract
Objective
To create the 3D convolutional neural network (CNN)-based system that can use whole-body FDG PET for recurrence/post-therapy surveillance in ovarian cancer (OC).
Methods
This study 1224 image sets from OC patients who underwent whole-body FDG PET/CT at Kowsar hospital between April 2019 and May 2022 were investigated. For recurrence/post-therapy surveillance, diagnostic classification as cancerous, and non-cancerous and staging as stage III, and stage IV were determined by pathological diagnosis and specialists’ interpretation. New deep neural network algorithms, the OCDAc-Net, and the OCDAs-Net were developed for diagnostic classification and staging of OC patients using PET/CT images. Examinations were divided into independent training (75%), validation (10%), and testing (15%) subsets.
Results
This study included 37 women (mean age, 56.3 years; age range, 36–83 years). Data augmentation techniques were applied to the images in two phases. There were 1224 image sets for diagnostic classification and staging. For the test set, 170 image sets were considered for diagnostic classification and staging. The OCDAc-Net areas under the receiver operating characteristic curve (AUCs) and overall accuracy for diagnostic classification were 0.990 and 0.92, respectively. The OCDAs-Net achieved areas under the receiver operating characteristic curve (AUCs) of 0.995 and overall accuracy of 0.94 for staging.
Conclusions
The proposed 3D CNN-based models provide potential tools for recurrence/post-therapy surveillance in OC. The OCDAc-Net and the OCDAs-Net model provide a new prognostic analysis method that can utilize PET images without pathological findings for diagnostic classification and staging.
Second-order Rosenbrock-Exponential (ROSEXP) Methods for Partitioned Differential Equations
Authors: Dallerit Valentin , Buvoli Tommaso , Tokman Mayya , Gaudreault Stéphane 
Published: June 2023

Abstract
In this paper, we introduce a new framework for deriving partitioned implicit-exponential integrators for stiff systems of ordinary differential equations and construct several time integrators of this type. The new approach is suited for solving systems of equations where the forcing term is comprised of several additive nonlinear terms. We analyze the accuracy and stability of the new integrators and compare their performance with existing schemes for such systems using several numerical examples. We also propose a novel approach to visualizing the linear stability of the partitioned schemes, which provides a more intuitive way to understand and compare the stability properties of various schemes. Our new integrators are A-stable, 2nd order methods that require only one call to the linear system solver and one exponential-like matrix function evaluation per time step. In addition to comparing the new integrators to previously proposed schemes, our numerical experiments validate the convergence and efficiency of the new methods.
Automated Cervical Cell Segmentation using Deep Ensemble Learning
Authors: Ji Jie , Zhang Weifeng , Dong Yuejiao , Lin Ruilin , Geng Yiqun , Hong Liangli 
Published: June 2023

Abstract
Background
Cervical cell segmentation is a fundamental step in automated cervical cancer cytology screening. The aim of this study was to develop and evaluate a deep ensemble model for cervical cell segmentation including both cytoplasm and nucleus segmentation.
Methods
The Cx22 dataset was used to develop the automated cervical cell segmentation algorithm.The U-Net, U-Net++, DeepLabV3, DeepLabV3Plus, Transunet, and Segformer were used as candidate model architectures, and each of the first four architectures adopted two different encoders choosing from resnet34, resnet50 and denseNet121. Models were trained under two settings: trained from scratch, encoders initialized from ImageNet pre-trained models and then all layers were fine-tuned. For every segmentation task, four models were chosen as base models, and Unweighted average was adopted as the model ensemble method.
Results
U-Net and U-Net + + with resnet34 and denseNet121 encoders trained using transfer learning consistently performed better than other models, so they were chosen as base models. The ensemble model obtained the Dice similarity coefficient, sensitivity, specificity of 0.9535 (95% CI:0.9534–0.9536) ,0.9621 (0.9619–0.9622) ,0.9835 (0.9834–0.9836) and 0.7863 (0.7851–0.7876) ,0.9581 (0.9573–0.959), 0.9961 (0.9961–0.9962) on cytoplasm segmentation and nucleus segmentation, respectively. Except for the specificity of cytoplasm segmentation, all metrics outperformed the best baseline models(P < 0.05) with a moderate margin.
Conclusions
The proposed algorithm achieved better performances on cervical cell segmentation. It can be potentially used in automated cervical cancer cytology screening system.