bluuebunny/crossref_metadata_2025_split huggingface dataset:
Color vision evolution in egg-laying mammals: insights from visual photoreceptors and daily activities of Australian echidnas
Authors: Sakamoto Shiina , Matsushita Yuka , Itoigawa Akihiro , Ezawa Takumi , Fujitani Takeshi , Takakura Kenichiro , Zhou Yang , Zhang Guojie , Grutzner Frank , Kawamura Shoji , Hayakawa Takashi 
Published: January 2024

AbstractEgg-laying mammals (monotremes) are considered “primitive” due to traits such as oviparity, cloaca, and incomplete homeothermy, all of which they share with reptiles. Two groups of monotremes, the terrestrial echidna (Tachyglossidae) and semiaquatic platypus (Ornithorhynchidae), have evolved highly divergent characters since their emergence in the Cenozoic era. These evolutionary differences, notably including distinct electrosensory and chemosensory systems, result from adaptations to species-specific habitat conditions. To date, very few studies have examined the visual adaptation of echidna and platypus. In the present study, we show that echidna and platypus have different light absorption spectra in their dichromatic visual sensory systems at the molecular level. We analyzed absorption spectra of monotreme color opsins, long-wavelength sensitive opsin (LWS) and short-wavelength sensitive opsin 2 (SWS2). The wavelength of maximum absorbance (λmax) in LWS was 570.2 in short-beaked echidna (Tachyglossus aculeatus) and 560.6 nm in platypus (Ornithorhynchus anatinus); in SWS2, λmax was 451.7 and 442.6 nm, respectively. Thus, the spectral range in echidna color vision is ~ 10 nm longer overall than in platypus. Natural selection analysis showed that the molecular evolution of monotreme color opsins is generally functionally conserved, suggesting that these taxa rely on species-specific color vision. In order to understand the usage of color vision in monotremes, we made 24-h behavioral observations of captive echidnas at warm temperatures and analyzed the resultant ethograms. Echidnas showed cathemeral activity and various behavioral repertoires such as feeding, traveling, digging, and self-grooming without light/dark environment selectivity. Halting (careful) behavior is more frequent in dark conditions, which suggests that echidnas may be more dependent on vision during the day and olfaction at night. Color vision functions have contributed to dynamic adaptations and dramatic ecological changes during the ~ 60 million years of divergent monotreme evolution. The ethogram of various day and night behaviors in captive echidnas also contributes information relevant to habitat conservation and animal welfare in this iconic species, which is locally endangered.
Exploring the determinants of the user experience in P2P payment systems in Spain: a text mining approach
Authors: Perea-Khalifi David , Irimia-Diéguez Ana I. , Palos-Sánchez Pedro 
Published: January 2024

Abstract
Purpose
This study aims to identify which determinants are responsible for impacting the user experience of three peer-to-peer (P2P) payment services in the Spanish market.

Design/methodology/approach
A sample of all online reviews (n = 16,048) published in Google Play of three paytech apps—Bizum, Twyp, and Verse—was analyzed using text mining and sentiment analysis.

Findings
A holistic interpretation of the seed terms included in each aspect allowed to label them based on the preferences expressed by paytech app users in their reviews. Six latent aspects were identified: ease of use, usefulness, perceived value, performance expectancy, perceived quality, and user experience. In addition, the results of the analysis suggest a positivity bias in the online reviews of fintech P2P app users. Our results also show that online reviews of apps associated with banks or financial institutions, such as Bizum (to a greater extent) or Twyp, show more negative emotions, whereas independent apps (Verse) show more positive emotions. Moreover, the most critical users are those of unidentified gender, while women remain in a more neutral position, and men tend to express their opinions more positively regarding P2P payment apps.

Practical implications
Paytech providers should analyze the problems faced by users immediately after an encounter. By applying text mining analysis, service providers can gain efficiency in understanding user sentiments and emotions without tedious and time-consuming reviews.

Originality/value
This is a pioneering study on peer-to-peer (P2P) mobile payment systems from the user’s perspective because it investigates the emotions and sentiments that users convey through bank reviews.
Effect of low sodium and high potassium diet on lowering blood pressure and cardiovascular events
Authors: Kim Byung Sik , Yu Mi-Yeon , Shin Jinho 
Published: January 2024

AbstractIncorporating aggressive lifestyle modifications along with antihypertensive medication therapy is a crucial treatment strategy to enhance the control rate of hypertension. Dietary modification is one of the important lifestyle interventions for hypertension, and it has been proven to have a clear effect. Among food ingredients, sodium and potassium have been found to have the strongest association with blood pressure. The blood pressure-lowering effect of a low sodium diet and a high potassium diet has been well established, especially in hypertensive population. A high intake of potassium, a key component of the Dietary Approaches to Stop Hypertension (DASH) diet, has also shown a favorable impact on the risk of cardiovascular events. Additionally, research conducted with robust measurement methods has shown cardiovascular benefits of low-sodium intake. In this review, we aim to discuss the evidence regarding the relationship between the low sodium and high potassium diet and blood pressure and cardiovascular events.
Graphical Abstract
A deep learning model integrating multisequence MRI to predict EGFR mutation subtype in brain metastases from non-small cell lung cancer
Authors: Li Ye , Lv Xinna , Chen Cancan , Yu Ruize , Wang Bing , Wang Dawei , Hou Dailun 
Published: January 2024

Abstract
Background
To establish a predictive model based on multisequence magnetic resonance imaging (MRI) using deep learning to identify wild-type (WT) epidermal growth factor receptor (EGFR), EGFR exon 19 deletion (19Del), and EGFR exon 21-point mutation (21L858R) simultaneously.

Methods
A total of 399 patients with proven brain metastases of non-small cell lung cancer (NSCLC) were retrospectively enrolled and divided into training (n = 306) and testing (n = 93) cohorts separately based on two timepoints. All patients underwent 3.0-T brain MRI including T2-weighted, T2-weighted fluid-attenuated inversion recovery, diffusion-weighted imaging, and contrast-enhanced T1-weighted sequences. Radiomics features were extracted from each lesion based on four sequences. An algorithm combining radiomics approach with graph convolutional networks architecture (Radio-GCN) was designed for the prediction of EGFR mutation status and subtype. The area under the curve (AUC) at receiver operating characteristic analysis was used to evaluate the predication capabilities of each model.

Results
We extracted 1,290 radiomics features from each MRI sequence. The AUCs of the Radio-GCN model for identifying EGFR 19Del, 21L858R, and WT for the lesion-wise analysis were 0.996 ± 0.004, 0.971 ± 0.013, and 1.000 ± 0.000 on the independent testing cohort separately. It also yielded AUCs of 1.000 ± 0.000, 0.991 ± 0.009, and 1.000 ± 0.000 for predicting EGFR mutations respectively for the patient-wise analysis. The κ coefficients were 0.735 and 0.812, respectively.

Conclusions
The constructed Radio-GCN model is a new potential tool to predict the EGFR mutation status and subtype in NSCLC patients with brain metastases.

Relevance statement
The study demonstrated that a deep learning approach based on multisequence MRI can help to predict the EGFR mutation status in NSCLC patients with brain metastases, which is beneficial to guide a personalized treatment.

Key points
• This is the first study to predict the EGFR mutation subtype simultaneously.
• The Radio-GCN model holds the potential to be used as a diagnostic tool.
• This study provides an imaging surrogate for identifying the EGFR mutation subtype.

Graphical Abstract
Automated pelvic MRI measurements associated with urinary incontinence for prostate cancer patients undergoing radical prostatectomy
Authors: van den Berg Ingeborg , Spaans Robert N. , Wessels Frank J. , van der Hoeven Erik J. R. J. , Nolthenius Charlotte J. Tutein , van den Bergh Roderick C. N. , van der Voort van Zyp Jochem R. N. , van den Berg Cornelis A. T. , van Melick Harm H. E. 
Published: January 2024

Abstract
Background
Pelvic morphological parameters on magnetic resonance imaging (MRI), such as the membranous urethral length (MUL), can predict urinary incontinence after radical prostatectomy but are prone to interobserver disagreement. Our objective was to improve interobserver agreement among radiologists in measuring pelvic parameters using deep learning (DL)-based segmentation of pelvic structures on MRI scans.

Methods
Preoperative MRI was collected from 167 prostate cancer patients undergoing radical prostatectomy within our regional multicentric cohort. Two DL networks (nnU-Net) were trained on coronal and sagittal scans and evaluated on a test cohort using an 80/20% train-test split. Pelvic parameters were manually measured by three abdominal radiologists on raw MRI images and with the use of DL-generated segmentations. Automated measurements were also performed for the pelvic parameters. Interobserver agreement was evaluated using the intraclass correlation coefficient (ICC) and the Bland–Altman plot.

Results
The DL models achieved median Dice similarity coefficient (DSC) values of 0.85–0.97 for coronal structures and 0.87–0.98 for sagittal structures. When radiologists used DL-generated segmentations of pelvic structures, the interobserver agreement for sagittal MUL improved from 0.64 (95% confidence interval 0.28–0.83) to 0.91 (95% CI 0.84–0.95). Furthermore, there was an increase in ICC values for the obturator internus muscle from 0.74 (95% CI 0.42–0.87) to 0.86 (95% CI 0.75–0.92) and for the levator ani muscle from 0.40 (95% CI 0.05–0.66) to 0.61 (95% CI 0.31–0.78).

Conclusions
DL-based automated segmentation of pelvic structures improved interobserver agreement in measuring pelvic parameters on preoperative MRI scans.

Relevance statement
The implementation of deep learning segmentations allows for more consistent measurements of pelvic parameters by radiologists. Standardized measurements are crucial for incorporating these parameters into urinary continence prediction models.

Key points
• DL-generated segmentations improve interobserver agreement for pelvic measurements among radiologists.
• Membranous urethral length measurement improved from substantial to almost perfect agreement.
• Artificial intelligence enhances objective pelvic parameter assessment for continence prediction models.

Graphical Abstract
Utility of dipstick urinalysis in the diagnosis of urinary tract infections among outpatients in Mwanza and Dar es Salaam regions in Tanzania
Authors: Masoud Salim S. , Majigo Mtebe , Silago Vitus , Kunambi Peter , Nyawale Helmut , Moremi Nyambura , Komba Erick , Mgaya Fauster X. , Magembe Emmanuel , Mirambo Mariam M. , Mshana Stephen E. , Matee Mecky Isaac 
Published: January 2024

Abstract
Background
Globally, urinary tract infections (UTIs) are the leading cause of hospital visits, especially among women. In many developing countries, especially in lower health facilities, the dipstick urinalysis is the most commonly requested test, as urine culture is not routinely performed. The dipstick test can potentially reduce the number of patients who could be treated with empirical antibiotics and reduce the burden of antibiotic resistance. The current study determined the utility of dipstick urinalysis in diagnosing UTIs using urine culture as a gold standard method.

Methods
A cross-sectional study was conducted between July and November 2021. The study involved 1327 outpatients attending lower health centres in Mwanza (n = 678) and Dar es Salaam (n = 649) regions. The samples were subjected to dipstick urinalysis (nitrite and leucocytes) and quantitative bacterial culture.

Results
Of all 1326 patient samples, 808(60.9%) and 48(3.6%) were positive for urinary leucocyte and nitrite, respectively, while significant urine culture was found in 364(27.4%). leucocyte test correctly diagnosed UTI in 283 (77.75%) and nitrite test in 36 (9.89%). The leucocytes and nitrites, in combination, exhibited a sensitivity of 79.40% and NPV of 85.24% but a lower specificity of 44.96% and a lower PPV of 35.29%. Urinary leucocyte test had a higher discrimination ability to detect urinary tract infection than urinary nitrite test (AUC = 0.073, 95% CI 0.043–0.103, p < 0.001); likewise, combined results of urinary nitrite and leucocytes tests had higher discrimination ability to detect UTI than nitrite only (AUC = − 0.079, 95% CI − 0.107–0.050, p < 0.001).

Conclusions
In settings where culture is available, dipstick urinalysis can be a helpful screening method for reducing unnecessary urine cultures and related expenses because of its higher negative predictive value. In most low-resource settings where patients' diagnosis solely depends on clinical diagnosis and culture is not easily available, urine dipstick can decrease the risk of overuse of antibiotics. However, the combined (leucocytes and nitrites) dipstick urinalysis has a rather low positive predictive value, with approximately one-third of cases giving positive test results being truly UTI, subjecting over 65% of cases to unnecessary antibiotic treatment.
Optimising Al2O3–water nanofluid
Authors: Onyiriuka Ekene 
Published: January 2024

Abstract
Background
This study explores how nanofluids can be optimised to improve heat transfer in various applications. A genetic algorithm that finds the optimal parameter configuration to achieve the best performance is studied and applied. The research focuses on the critical factors of heat transfer coefficient and pressure drop, which determine the efficiency of nanofluid-based systems.

The main body of the abstract
The methodology involves artificial intelligence and multi-objective optimisation techniques. Results show that pressure drop and heat transfer coefficient have an inverse relationship. The study provides a range of optimal values for nanofluid temperature, particle size, and volume fraction.

Results
The results show that the temperature, particle size, and volume fraction should be high. Another variation will be small particle size and small volume fractions with fluid temperature around 80 °C. The analysis yielded the following configuration with the optimal PEC. Temperature (oC), particle size (nm), volume fraction (%), heat transfer coefficient (kW/m2K), pressure drop (Pas), and PEC were 82.6 °C, 175.26 nm, 4.75%, 792.49 kW/m2K, 29.94 Pas, and 5.01.

Conclusions
The research highlights the potential of Al2O3–water nanofluids to maintain pressure drop and enhance heat transfer. It contributes to understanding nanofluid optimisation and provides practical insights for designing and selecting nanofluid systems that enhance heat transfer.
What is known about the effects of vitamin D in neuropsychiatric lupus?
Authors: Karnopp Thaís Evelyn , da Silva Freitas Vinicius , Di Domenico Andressa Leite , Chapacais Gustavo Flores , dos Santos Natália Garcia , Freitas Eduarda Correa , Gasparin Andrese Aline , Monticielo Odirlei André 
Published: January 2024

AbstractSystemic lupus erythematosus (SLE) is an autoimmune disease that can affect several organs and systems. The central and/or peripheral nervous system can suffer from complications known as neuropsychiatric lupus (NPSLE). Studies have associated the manifestations of SLE or NPSLE with vitamin D deficiency. It has been shown that hypovitaminosis D can lead to cognition deficits and cerebral hypoperfusion in patients with NPSLE. In this review article, we will address the main features related to vitamin D supplementation or serum vitamin D levels with neuropsychiatric manifestations, either in patients or in animal models of NPSLE.
Graphical abstract
BRITD: behavior rhythm insider threat detection with time awareness and user adaptation
Authors: Song Shuang , Gao Neng , Zhang Yifei , Ma Cunqing 
Published: January 2024

AbstractResearchers usually detect insider threats by analyzing user behavior. The time information of user behavior is an important concern in internal threat detection. Existing works on insider threat detection fail to make full use of the time information, which leads to their poor detection performance. In this paper, we propose a novel behavioral feature extraction scheme: we implicitly encode absolute time information in the behavioral feature sequences and use a feature sequence construction method taking covariance into account to make our scheme adaptive to users. We select Stacked Bidirectional LSTM and Feedforward Neural Network to build a deep learning-based insider threat detection model: Behavior Rhythm Insider Threat Detection (BRITD). BRITD is universally applicable to various insider threat scenarios, and it has good insider threat detection performance: it achieves an AUC of 0.9730 and a precision of 0.8072 with the CMU CERT dataset, which exceeds all baselines.
Graphical Abstract
Corner cases in machine learning processes
Authors: Heidecker Florian , Bieshaar Maarten , Sick Bernhard 
Published: January 2024

AbstractApplications using machine learning (ML), such as highly autonomous driving, depend highly on the performance of the ML model. The data amount and quality used for model training and validation are crucial. If the model cannot detect and interpret a new, rare, or perhaps dangerous situation, often referred to as a corner case, we will likely blame the data for not being good enough or too small in number. However, the implemented ML model and its associated architecture also influence the behavior. Therefore, the occurrence of prediction errors resulting from the ML model itself is not surprising. This work addresses a corner case definition from an ML model’s perspective to determine which aspects must be considered. To achieve this goal, we present an overview of properties for corner cases that are beneficial for the description, explanation, reproduction, or synthetic generation of corner cases. To define ML corner cases, we review different considerations in the literature and summarize them in a general description and mathematical formulation, whereby the expected relevance-weighted loss is the key to distinguishing corner cases from common data. Moreover, we show how to operationalize the corner case characteristics to determine the value of a corner case. To conclude, we present the extended taxonomy for ML corner cases by adding the input, model, and deployment levels, considering the influence of the corner case properties.
Scopoletin negatively regulates the HOG pathway and exerts antifungal activity against Botrytis cinerea by interfering with infection structures, cell wall, and cell membrane formation
Authors: Yuan Xiaojun , Yang Fugen , Wang Yameng , Li Shaoxuan , Zhang Demeng , Liang Wenxing , Yang Qianqian 
Published: January 2024

AbstractBotrytis cinerea is the causative agent of gray mold, a fungal disease affecting a broad array of food crops and resulting in considerable agricultural and economic losses. Currently, chemical fungicides are the most effective control measure, but this practice is challenged by the growing resistance of pathogens to these fungicides. Scopoletin, a major phytoalexin of tobacco plants, has shown promise as an antifungal treatment. Here, we found that scopoletin was effective against B. cinerea infection of tomato leaves. It inhibited mycelial growth and conidial germination of B. cinerea and disrupted cell wall, cell membrane, and infection structure formation. Transcriptomic analysis identified 3495 differentially expressed genes in response to scopoletin treatment. Interestingly, scopoletin seems to deactivate the HOG pathway of B. cinerea. The growth defect caused by hyperactivation of the pathway, such as iprodione treatment and deletion of BcPtc1, the negative regulator of this pathway, was partly rescued by scopoletin. Moreover, it could downregulate phosphorylation levels of BcSak1 treated with iprodione and NaCl. In addition, the control efficiency of triadimefon was significantly increased by scopoletin. Thus, scopoletin is a promising, naturally derived, and sustainable treatment for gray mold, especially when combined with triadimefon.
A simple and rapid preparation of smooth muscle myosin 2 for the electron microscopic analysis
Authors: Bharda Anahita Vispi , Jung Hyun Suk 
Published: January 2024

AbstractThere has been an increase in the demand for purified protein as a result of recent developments in the structural biology of myosin 2. Although promising, current practices in myosin purification are usually time-consuming and cumbersome. The reported increased actin to myosin ratio in smooth muscles adds to the complexity of the purification process. Present study outlines a streamlined approach to isolate smooth muscle myosin 2 molecules from actomyosin suspension of chicken gizzard tissues. The procedure entails treating actomyosin for a brief period with actin-binding peptide phalloidin, followed by co-sedimentation and short column size exclusion chromatography. Typical myosin molecule with heavy and light chains and approximately 95% purity was examined using gel electrophoresis. Negative staining electron microscopy and image processing showed intact 10S myosin 2 molecules, proving that phalloidin is effective at eliminating majority of actin in the form of F-actin without dramatic alteration in the structure of myosin. The entire purification discussed here can be completed in a few hours, and further analysis can be done the same day. Thus, by offering quick and fresh supplies of native myosin molecules suited for structural research, specially cryo-electron microscopy, this innovative approach can be adapted to get around the drawbacks of time-intensive myosin purifying processes.