bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gut microbial metabolites reveal diet-dependent metabolic changes induced by nicotine administration
Authors: Ohue-Kitano Ryuji , Banno Yukika , Masujima Yuki , Kimura Ikuo 
Published: January 2024

AbstractThe gut microbiota has emerged as an important factor that potentially influences various physiological functions and pathophysiological processes such as obesity and type 2 diabetes mellitus. Accumulating evidence from human and animal studies suggests that gut microbial metabolites play a critical role as integral molecules in host–microbe interactions. Notably, several dietary environment-dependent fatty acid metabolites have been recognized as potent modulators of host metabolic homeostasis. More recently, nicotine, the primary active molecule in tobacco, has been shown to potentially affect host metabolism through alterations in the gut microbiota and its metabolites. However, the mechanisms underlying the interplay between host nutritional status, diet-derived microbial metabolites, and metabolic homeostasis during nicotine exposure remain unclear. Our findings revealed that nicotine administration had potential effects on weight regulation and metabolic phenotype, independent of reduced caloric intake. Moreover, nicotine-induced body weight suppression is associated with specific changes in gut microbial composition, including Lactobacillus spp., and KetoB, a nicotine-sensitive gut microbiota metabolite, which could be linked to changes in host body weight, suggesting its potential role in modulating host metabolism. Our findings highlight the remarkable impact of the interplay between nutritional control and the gut environment on host metabolism during smoking and smoking cessation.
Transcription factor FoxO1 regulates myoepithelial cell diversity and growth
Authors: Tokumasu Rino , Yasuhara Rika , Kang Seya , Funatsu Takahiro , Mishima Kenji 
Published: January 2024

AbstractSalivary gland myoepithelial cells regulate saliva secretion and have been implicated in the histological diversity of salivary gland tumors. However, detailed functional analysis of myoepithelial cells has not been determined owing to the few of the specific marker to isolate them. We isolated myoepithelial cells from the submandibular glands of adult mice using the epithelial marker EpCAM and the cell adhesion molecule CD49f as indicators and found predominant expression of the transcription factor FoxO1 in these cells. RNA-sequence analysis revealed that the expression of cell cycle regulators was negatively regulated in FoxO1-overexpressing cells. Chromatin immunoprecipitation analysis showed that FoxO1 bound to the p21/p27 promoter DNA, indicating that FoxO1 suppresses cell proliferation through these factors. In addition, FoxO1 induced the expression of ectodysplasin A (Eda) and its receptor Eda2r, which are known to be associated with X-linked hypohidrotic ectodermal dysplasia and are involved in salivary gland development in myoepithelial cells. FoxO1 inhibitors suppressed Eda/Eda2r expression and salivary gland development in primordial organ cultures after mesenchymal removal. Although mesenchymal cells are considered a source of Eda, myoepithelial cells might be one of the resources of Eda. These results suggest that FoxO1 regulates myoepithelial cell proliferation and Eda secretion during salivary gland development in myoepithelial cells.
Pinch force sense test–retest reliability evaluation using contralateral force matching task
Authors: Li Lin , Li Shuwang 
Published: January 2024

AbstractA high test–retest reliability in measurement of pinch force sense is required to assess a clinical parameter accurately over a longitudinal study. Ipsilateral reproduction (IR) task and contralateral matching (CM) task have commonly been used for the assessment of force sense. To date, there has been little research on the test–retest reliability of pinch force sense utilizing the contralateral force matching task. This research aimed to explore this phenomenon across a spectrum of reference force levels (10, 30, and 50 percent maximum voluntary isometric contraction (MVIC)) using a contralateral matching task. Every participant in the study was tested twice by the same skilled experts, with each session separated by one week. Although normalized variable error indicated a poor level of reliability (intraclass correlation coefficient (ICC) = − 0.25 to 0.05) for these force sense tests, normalized constant error (ICC = 0.76–0.85) and normalized absolute error (ICC = 0.61–0.81) results indicated a fair to good of reliability. The lower bound of 95% CI of ICC for NAE and NCE indicated fair test–retest reliability (0.41–0.69). These findings suggest that investigators can reasonably obtain a fair to good test–retest reliability when investigating pinch force sense using the contralateral matching task. The Bland–Altman plots, SEM, and MDD95% were lower at these lower reference force level (10% MVIC) compared to the level of higher reference forces (30% and 50% MVIC). Therefore, when the reference force level increases, the participant needs a larger NAE or NCE decrease to show that their pinch force sense has indeed improved.
A high-performance polymer composite column for coronavirus nucleic acid purification
Authors: Zarouri Akli , Barnes Aaron M. T. , Aboubakr Hamada , Thekkudan Novi Vinni , Dong Qiuchen , Nelson Andrew , Goyal Sagar , Abbas Abdennour 
Published: January 2024

AbstractHere, we report the development of a novel polymer composite (PC) purification column and kit. The performance of the PC columns was compared to conventional silica gel (SG) columns for the purification of nucleic acids from coronaviruses, including SARS-CoV-2, in 82 clinical samples. The results shows that PC-based purification outperforms silica gel (SG)-based purification by enabling a higher sensitivity (94%), accuracy (97%), and by eliminating false positives (100% specificity). The high specificity is critical for efficient patient triage and resource management during pandemics. Furthermore, PC-based purification exhibits three times higher analytical precision than a commonly used SG-based nucleic acid purification thereby enabling a more accurate quantification of viral loads and higher reproducibility.
Insights into the pattern of choroidal vascularity index changes in idiopathic macular hole
Authors: Xia Huaqin , Yang Jiarui , Hou Qingyi , Wu Xinchun , Wang Changguan , Li Xuemin 
Published: January 2024

AbstractThis retrospective study aimed to investigate the changes in choroidal vascularity index (CVI) before and after surgery for idiopathic macular hole (MH). Enhanced depth imaging optical coherence tomography (EDI-OCT) images were analyzed at baseline and at 1-week, 1-month, and 3-month postoperative visits. A total of 97 patients (97 eyes) were included in the study. At baseline, overall CVI and macular CVI showed negative correlation with axial length (AL) and positive correlation with central corneal thickness (CCT). There were no significant differences in macular CVI or overall CVI between affected and healthy eyes, as well as in subgroup analysis of different stages of macular CVI. Following surgery, there was a significant decrease in CVI at 1 week postoperatively, followed by a gradual recovery to baseline levels over time. The observed changes in CVI may be attributed to factors such as air tamponade, pressure changes, and photoreceptor metabolism. This study provides insights into the pattern of CVI changes associated with MH surgery. The findings suggest that stage 4 MH is associated with decreased macular CVI in affected eyes. These results contribute to a better understanding of the effects of surgery on choroidal blood flow in MH patients.
A single-center experience of non-bioartificial DFAPP support systems among Chinese patients with hyperlipidemic moderate/severe acute pancreatitis
Authors: Cheng Xianwen , Zhan Yanrong , Wang Zhendong , Wang Feng , Zeng Xia , Mao Ya , Liu YaoShun 
Published: January 2024

AbstractTo assess the clinical efficacy of Double Filtration Plasmapheresis (DFAPP), a novel blood purification method, in treating hyperlipidemic moderate/severe pancreatitis (HL-M/SAP). A total of 68 HL-M/SAP patients were enrolled in this study. The observation group, comprising 34 patients, received DFAPP treatment, while the control group underwent CVVH + PA treatment. We compared the efficacy changes between the two groups post-treatment. Patients treated with DFAPP showed significant improvements in clinical outcomes. After 72 h of DFAPP treatment, HL-M/SAP patients exhibited notably lower multiple organ failure scores and a reduced mortality rate compared to those in the CVVH + PA group. Triglyceride levels in HL-M/SAP patients treated with DFAPP for 48 h averaged 3.75 ± 1.95, significantly lower than the 9.57 ± 3.84 levels in the CVVH + PA group (P < 0.05). Moreover, CRP levels decreased markedly, IL-17 levels diminished, IL-10 levels increased, and the decline in IL-35 levels was significantly less pronounced compared to the CVVH + PA group. The recurrence rate of pancreatitis was also significantly lower after 6 months. The early implementation of DFAPP in HL-M/SAP patients effectively reduces triglyceride levels, suppresses pro-inflammatory factors, enhances anti-inflammatory factors, and mitigates cytokine storm-induced sepsis damage. Consequently, this leads to a decrease in the incidence of multiple organ failure, improved patient survival rates, and a reduce the recurrence rate of lipogenic pancreatitis.Trial registration: Chinese Clinical Trial Registry, ChiCTR2300076066.
Genomic prediction in multi-environment trials in maize using statistical and machine learning methods
Authors: Barreto Cynthia Aparecida Valiati , das Graças Dias Kaio Olimpio , de Sousa Ithalo Coelho , Azevedo Camila Ferreira , Nascimento Ana Carolina Campana , Guimarães Lauro José Moreira , Guimarães Claudia Teixeira , Pastina Maria Marta , Nascimento Moysés 
Published: January 2024

AbstractIn the context of multi-environment trials (MET), genomic prediction is proposed as a tool that allows the prediction of the phenotype of single cross hybrids that were not tested in field trials. This approach saves time and costs compared to traditional breeding methods. Thus, this study aimed to evaluate the genomic prediction of single cross maize hybrids not tested in MET, grain yield and female flowering time. We also aimed to propose an application of machine learning methodologies in MET in the prediction of hybrids and compare their performance with Genomic best linear unbiased prediction (GBLUP) with non-additive effects. Our results highlight that both methodologies are efficient and can be used in maize breeding programs to accurately predict the performance of hybrids in specific environments. The best methodology is case-dependent, specifically, to explore the potential of GBLUP, it is important to perform accurate modeling of the variance components to optimize the prediction of new hybrids. On the other hand, machine learning methodologies can capture non-additive effects without making any assumptions at the outset of the model. Overall, predicting the performance of new hybrids that were not evaluated in any field trials was more challenging than predicting hybrids in sparse test designs.
Imaging cancer metabolism using magnetic resonance
Authors: Brindle Kevin M. 
Published: January 2024

AbstractThe challenge in clinical oncology is to select the most appropriate treatment for an individual patient. Transcriptome and metabolite profiling have revealed that tumours can display metabolic subtypes with different therapeutic vulnerabilities1–4. Metabolic imaging has the potential to distinguish these subtypes and therefore those treatment(s) that should be most effective. Moreover, since changes in tumour metabolism can occur early during treatment, metabolic imaging can also be used subsequently to detect early evidence of treatment response. In this Perspective I briefly review and discuss the relative advantages and disadvantages of magnetic resonance imaging of tumour metabolism using hyperpolarized 13C- and 2H-labelled substrates.
Transcriptome-based analysis of candidate gene markers associated with resistance mechanism to Phytophthora melonis that causes root and crown rot in pumpkin
Authors: Najafi Mohammadhadi , Nasr-Esfahani Mehdi , Vatandoost Jafar , Hassanzade-Khankahdani Hamed , Jami Moeini Matin 
Published: January 2024

Root and crown rot incited by an oomycete, Phytophthora melonis, causes significant yield losses in commercial pumpkin (Cucurbita pepo) production worldwide. Currently, resistant cultivars and knowledge of molecular mechanism of C. pepo against P. melonis are scarce. Here, we analysed the quantitative gene expression changes of 10 candidate gene markers (bHLH87, ERF014, HSF, MYB, PR-1, WRKY21, CPI, POD, PSK, SGT) in pumpkin roots and leaves at three time points (h post-inoculation, hpi) following inoculation with P. melonis in two resistant (Ghelyani and Tanbal), and two susceptible (Marmari and Khoreshti) varieties of pumpkin. Gene expression using quantitative real time PCR along a time course revealed the strongest transcriptomic response at 48 and 72 hpi in resistant genotypes, 1.1–2.7-fold in roots and leaves, respectively, with a high significant correlation (r = 0.857**−0.974**). We also found that CPI, PSK, SGT1 and POD act as a dual regulator that similarly modulate immunity not only against P. melonis, but also against other diseases such as early blight (Alternaria cucumerina), powdery mildew (Podosphaera xanthii), downy mildews (Pseudoperonospora cubensis), and pathogenic plant nematodes (Meloidogyne javanica). Furthermore, significantly higher activities of the ROS scavenging defence enzymes, catalase (1.6-fold increase) and peroxidase (6-fold increase) were observed in the roots of resistant cultivars at different hpi compared with non-inoculated controls. In addition, the biomass growth parameters including leaf and root length, stem and root diameter, root fresh weight and volume were significantly different among studied genotypes. Cumulatively, the transcriptome data provide novel insights into the response of pumpkins for improving pumpkin breeding to P. melonis.
A pedagogical note on teaching L2 prosody and speech sounds using hand gestures
Authors: Li Peng , Baills Florence , Alazard-Guiu Charlotte , Baqué Lorraine , Prieto Pilar 
Published: January 2024

Abstract
This paper reports the pedagogical decisions in Li et al. (2023) “The
effectiveness of embodied prosodic training in L2 accentedness and vowel accuracy” published in Second Language
Research. The study revealed that embodied prosodic training improved the overall pronunciation skills of
Catalan-speaking learners of French and the pronunciation accuracy of front rounded vowels more than training without hand
gestures. Three main pedagogical innovations were key in obtaining the positive results. First, the hand gestures performed by the
instructor closely mimicked the prosodic structure (i.e., the melodic and rhythmic features) of the target sentences. Second, the
sentences used for training were embedded in meaningful communicative dialogues. Third, the challenging L2 sounds were embedded in
multiple occasions and in various prosodic positions. Therefore, in the hope of encouraging L2 teachers to incorporate such
techniques in teaching practice, we provide a full description of the materials and procedures in Li et al. (2023).
Cluster profiles from beyond-the-QE CMB lensing mass maps
Authors: Saha Sayan , Legrand Louis , Carron Julien 
Published: January 2024

Abstract
Clusters of galaxies, being the largest collapsed structures in the universe, offer valuable insights into the nature of cosmic evolution. Precise calibration of the mass of clusters can be obtained by extracting their gravitational lensing signal on the Cosmic Microwave Background (CMB) fluctuations. We extend and test here the performance achieved on cluster scales by the parameter-free, maximum a posteriori (MAP) CMB lensing reconstruction method, which has been shown to be optimal in the broader context of CMB lensing mass map and power spectrum estimation. In the context of cluster lensing, the lensing signal of other large-scale structures acts as an additional source of noise. We show here that by delensing the CMB fluctuations around each and every cluster, this noise variance is reduced according to expectations. We also demonstrate that the well-known bias in the temperature quadratic estimator in this regime, sourced by the strong non-Gaussianity of the signal, is almost entirely mitigated without any scale cuts. Being statistically speaking an optimal and blind lensing mass map reconstruction, the MAP estimator is a promising tool for the calibration of the masses of clusters.
Turning kinematics of the scyphomedusa Aurelia aurita
Authors: Costello J H , Colin S P , Gemmell B J , Dabiri J O , Kanso E A 
Published: January 2024

Abstract
Scyphomedusae are widespread in the oceans and their swimming has provided valuable insights into the hydrodynamics of animal propulsion. Most of this research has focused on symmetrical, linear swimming. However, in nature, medusae typically swim circuitous, nonlinear paths involving frequent turns. Here we describe swimming turns by the scyphomedusa Aurelia aurita during which asymmetric bell margin motions produce rotation around a linearly translating body center. These jellyfish ‘skid’ through turns and the degree of asynchrony between opposite bell margins is an approximate predictor of turn magnitude during a pulsation cycle. The underlying neuromechanical organization of bell contraction contributes substantially to asynchronous bell motions and inserts a stochastic rotational component into the directionality of scyphomedusan swimming. These mechanics are important for natural populations because asynchronous bell contraction patterns are common in situ and result in frequent turns by naturally swimming medusae.
Mechanical modeling of mechanosensitive insect strain sensors as a tool to investigate exoskeletal interfaces
Authors: Dinges Gesa F , Zyhowski William P , Lucci Anastasia , Friend Jordan , Szczecinski Nicholas S 
Published: January 2024

Abstract
During walking, sensory information is measured and monitored by sensory organs that can be found on and within various limb segments. Strain can be monitored by insect load sensors, campaniform sensilla (CS), which have components embedded within the exoskeleton. CS vary in eccentricity, size, and orientation, which can affect their sensitivity to specific strains. Directly investigating the mechanical interfaces that these sensors utilize to encode changes in load bears various obstacles, such as modeling of viscoelastic properties. To circumvent the difficulties of modeling and performing biological experiments in small insects, we developed 3-dimensional printed resin models based on high-resolution imaging of CS. Through the utilization of strain gauges and a motorized tensile tester, physiologically plausible strain can be mimicked while investigating the compression and tension forces that CS experience; here, this was performed for a field of femoral CS in Drosophila melanogaster. Different loading scenarios differentially affected CS compression and the likely neuronal activity of these sensors and elucidate population coding of stresses acting on the cuticle.
Spatiotemporal variations and its driving factors of ground surface temperature in China
Authors: Gao Xin , Huang Liyan , Zhang Jingwen , Lin Kairong , Li Pengjun 
Published: January 2024

Abstract
The ground surface temperature (GST) serves as a crucial indicator for understanding land-atmosphere mass and energy exchange. The shift from manual measurement to automated station for GST in China after 2002 introduced inconsistencies at certain stations, potentially distorting research findings. Here, daily automatedly observed GST from 2003 to 2017 at 615 selected meteorological stations were updated by constructing linear regression model based on manually observed air temperature (AT) and GST from 1960 to 2002. Then, the spatiotemporal variations of GST from 1960 to 2017 and its driving factors were investigated. Results indicated that: (1) the AT-GST linear regression model could effectively mitigate the inconsistency caused by the change of GST observation methods, enhancing data reliability. (2) GST in China showed little change from 1960–1980, but increased significantly across all regions from 1980 to 2000, with the increase rate slowed down except in the Qinghai–Tibet plateau (QTP) and southwest China after 2000. Notable GST increase is concentrated in colder regions, including the QTP, northeast (NEC), and northwest China (NWC). (3) Evapotranspiration (ET) and vapor pressure deficit were the primary drivers of annual GST variations at the regional scale, while their contributions to GST variations exhibited notable seasonal variability. Our findings could offer valuable scientific insights for addressing climate change, enhancing surface environmental models, and safeguarding ecological environments.
Quod significat: Vitruvius’ ultimate criterion for (good) architecture
Authors: Lefas Pavlos 
Published: January 2024

Abstract
The present paper proposes a new reading of one of the most obscure passages of De Architectura; in I, 1,3 Vitruvius claims that in architecture there is always a signifier and a signified, but his approach differs from Quintilian’s as presented in the latter’s Institutio Oratoria. Vitruvius’ is closer to Chrysippus approach, but he fails to mention the third constituent, the tynchanon. This omission is probably due to the fact that Vitruvius speaks of designs rather, than of existing buildings. What can successfully signify a proposed building is, according to my reading, the design and erection of a building that is easily recognized by the public as realizing the intentions of the community to erect the proposed building. Such successful signification constitutes the ultimate criterion for good architecture.
methylClass: an R package to construct DNA methylation-based classification models
Authors: Liu Yu 
Published: January 2024

Abstract
DNA methylation profiling is a useful tool to increase the accuracy of a cancer diagnosis. However, a comprehensive R package specially for it is lacking. Hence, we developed the R package methylClass for methylation-based classification. Within it, we provide the eSVM (ensemble-based support vector machine) model to achieve much higher accuracy in methylation data classification than the popular random forest model and overcome the time-consuming problem of the traditional SVM. In addition, some novel feature selection methods are included in the package to improve the classification. Furthermore, because methylation data can be converted to other omics, such as copy number variation data, we also provide functions for multi-omics studies. The testing of this package on four datasets shows the accurate performance of our package, especially eSVM, which can be used in both methylation and multi-omics models and outperforms other methods in both cases. methylClass is available at: https://github.com/yuabrahamliu/methylClass.