bluuebunny/crossref_metadata_2025_split huggingface dataset:
An app promoting weight gain prevention via healthy behaviours amongst young women with a family history of breast cancer: Acceptability and usability assessment
Authors: Pegington Mary , Hawkes Rhiannon E. , Davies Alan , Mueller Julia , Howell Anthony , Gareth Evans D. , Howell Sacha J. , French David P. , Harvie Michelle 
Published: July 2024

AbstractBackgroundBreast cancer is the most frequent female malignancy in the UK. Around 20% of cases are linked to weight gain, excess weight and health behaviours. We designed a weight gain prevention, health behaviour intervention for young women at increased risk.MethodsThe study comprised a single arm observational study over 2 months testing acceptability and usability of the intervention: online group welcome event, app and private Facebook group. Females aged 18–35 years at moderate or high risk of breast cancer (>17% lifetime risk) were recruited via invite letters and social media posts. The app included behaviour change techniques and education content. Online questionnaires were completed at baseline, as well as at 1 and 2 months. We also assessed feasibility of study procedures.ResultsBoth recruitment methods were successful. Thirty‐five women were recruited, 26% via social media posts. Median age was 33 (interquartile range = 28.2–34.5) years, the majority (94.1%) were of White ethnicity. Thirty‐four participants were included in the analyses, of which 94% downloaded the app. Median self‐monitoring logs per participant during the study period was 10.0 (interquartile range = 4.8–28.8). App quality mean (SD) score was 3.7 (0.6) at 1 and 2 months (scale: 1–5). Eighty‐nine per cent rated the app at average or above at 1 month and 75.0% at 2 months. Nineteen women (55.9%) joined the Facebook group and there were 61 comments and 83 reactions and votes from participants during the study period.ConclusionsThis first iteration of the app and intervention was well received and is suitable to progress to the next stage of refining and further testing.
Tyndall, Rayleigh, Mei, and Raman scattering: Understanding their role in aesthetics
Authors: Humzah M. D. 
Published: July 2024

AbstractThe role of various light scattering phenomena in aesthetics and clinical practice is explored in this review. Four main types of light scattering, Tyndall, Rayleigh, Mie, and Raman, are discussed. Each type is explained in terms of its physical principles and its applications in aesthetic medicine. Tyndall scattering is relevant in understanding the blue appearance of certain dermal fillers. Rayleigh scattering contributes to skin tone perception and plays a role in certain laser treatments. Mie scattering is important in laser hair removal and the appearance of skin conditions like melasma. Raman scattering, while primarily used in research, shows promise for non‐invasive skin analysis, personalized skincare, treatment monitoring, and early skin cancer detection. It is important to understand these scattering phenomena for optimizing light‐based aesthetic procedures and developing effective treatments. Properly applying the appropriate scattering theory based on relative particle size is crucial in clinical aesthetic practice.
Model of predicting fear of cancer recurrence in patients with digestive tract cancer: A cross‐sectional study
Authors: Li Yaru , Wang Lei , Zhang Zhenhua , Zhang Xinyu , Yu Xiao , Ma Yanmei 
Published: July 2024

AbstractAimsTo investigate the incidence of fear of cancer recurrence in patients with digestive tract cancers analyse its influencing factors, and further establish a visual risk prediction model.DesignA cross‐sectional study.MethodsA cross‐sectional survey was conducted among 570 patients with digestive tract tumours admitted to a local hospital, from May 2023 to December 2023 by convenient sampling method. Univariate analysis and logistic analysis were performed on the influencing factors, and the risk prediction nomogram model of fear of cancer recurrence in patients with digestive tract cancer was constructed by using R 4.1.3 software. ROC curve was used to evaluate the differentiation of the nomogram model. The calibration curve and Hosmer‐Lemeshow goodness of fit test were used to evaluate the consistency of the model. This study was reported using the TRIPOD checklist.ResultsIn this study, 272 (47.7%) patients developed fear of recurrence. The risk prediction model of recurrence fear column chart for digestive tract cancer patients incorporated six variables of gender, therapy, alimentary tract haemorrhage, pain, depression and social support. The C‐statistic was (.976), and the calibration curve showed that the predicted probability was more in line with the actual probability of occurrence, and the decision curve showed that the predictive model had better practicality.ConclusionThe column‐line diagram prediction model constructed in this study is effective and facilitates timely intervention and management by healthcare professionals based on their risk factors.ImpactNomogram is helpful to calculate the risk probability of FCR in patients with digestive tract cancer, identify FCR patients in time, and formulate comprehensive and personalized countermeasures, to provide a good quality of life and prolong the survival cycle of patients with digestive tract cancer.Patient or Public ContributionParticipants were hospitalized patients or patients with digestive tract cancer undergoing follow‐up. First of all, before the investigation and research, a team is formed to discuss the concept, research purpose, method, significance, etc., and determine the research tools. Second, by reasonably explaining the study to patients to seek informed consent from the patient and sign it, patients filled in the questionnaire independently. For patients with low education levels who could not fill in the questionnaire, the team members made objective explanations to help them choose reasonable options.
Parotid saliva and blood biomarkers in juvenile idiopathic arthritis in relation to temporomandibular joint magnetic resonance imaging findings
Authors: Carlsson Alexandra Dimitrijevic , Wahlund Kerstin , Ghafouri Bijar , Kindgren Erik , Frodlund Martina , Salé Hanna , Klintström Eva , Johansson Carin Starkhammar , Alstergren Per 
Published: July 2024

AbstractBackgroundJuvenile idiopathic arthritis (JIA) often affects the temporomandibular joint (TMJ) caused by an abnormal immune system that includes overactive inflammatory processes. Salivary biomarkers may be a powerful tool that can help establishing diagnosis, prognosis and monitor disease progress.ObjectiveThe objective was to investigate biomarkers in parotid saliva and blood plasma in relation to temporomandibular joint (TMJ) magnetic resonance imaging (MRI) findings in patients with JIA and healthy individuals.MethodsForty‐five children aged 6 to 16 years with JIA and 16 healthy age‐ and sex‐matched controls were included. Unstimulated parotid saliva samples and venous blood were collected. Biochemical analyses were performed for the cytokine biomarkers. The participants underwent MR imaging of the TMJs, where changes in the inflammatory and the damage domains were assessed.ResultsIn the JIA patients, lower concentrations of IL‐6R and gp130 were found in parotid saliva than in plasma. Higher concentrations of IL‐6 were found in parotid saliva than in plasma. IL‐6, IL‐6R and gp130 in parotid saliva explained the presence of bone marrow oedema and effusion in the JIA patients.ConclusionsThis study suggests that the IL‐6 family in parotid saliva is associated with TMJ bone marrow oedema and effusion in patients with JIA, suggesting that IL‐6 has promising properties as a parotid saliva biomarker for TMJ inflammatory activity.
On the (robust) ex post stability of constitutions
Authors: Jeong Daeyoung , Kim Semin 
Published: July 2024

AbstractThis paper explores the concept of ex post stability in voting systems, shifting the focus from the traditional ex ante perspective, where preferences are uncertain, to a setting where agents' preferences are fully known. We offer a comprehensive characterization of ex post stable constitutions within deterministic voting rule environments. We bridge the theoretical gap between ex post and ex ante stability, shedding light on their intricate relationship and implications for the design and evolution of voting systems. Additionally, our research further evaluates the resilience of these constitutions to changes in the voting environment, particularly their flexibility in response to varying alternative rule sets. This study not only contributes to a deeper understanding of constitutional stability but also provides insights into the dynamics of collective decision‐making processes.
Azole resistance in Aspergillus flavus and associated fitness cost
Authors: Djenontin Elie , Debourgogne Anne , Mousavi Bita , Delhaes Laurence , Cornet Muriel , Valsecchi Isabel , Adebo Makiath , Guillot Jacques , Botterel Françoise , Dannaoui Eric 
Published: July 2024

AbstractBackgroundThe resistance of Aspergillus flavus to the azole antifungal drugs is an emerging problem. Mutations in the molecular targets of the azole antifungals ‐ CYP 51 A, B and C ‐ are possible mechanisms of resistance, but data to confirm this hypothesis are scarce. In addition, the behaviour of resistant strains in vitro and in vivo is not yet understood.ObjectivesThis study had 3 objectives. The first was to compare the sequences of CYP51 A, B and C in resistant and susceptible strains of A. flavus. The second was to look for the existence of a fitness cost associated with resistance. The third was to evaluate the activity of voriconazole and posaconazole on resistant strains in the Galleria mellonella model.MethodsThe CYP51 A, B and C sequences of seven resistant strains with those of four susceptible strains are compared. Fitness costs were assessed by growing the strains in RPMI medium and testing their virulence in G. mellonella larvae. In addition, G. mellonella larvae infected with strains of A. flavus were treated with voriconazole and posaconazole.ResultsIn the CYP51A sequences, we found the A91T, C708T and A1296T nucleotide substitutions only in the resistant strains. The resistant strains showed a fitness cost with reduced in vitro growth and reduced virulence in G. mellonella. In vivo resistance to posaconazole is confirmed in a strain with the highest MIC for this antifungal agent.ConclusionsThese results allow to conclude that some substitutions in CYP51 genes, in particular CYP51A, contribute to resistance to azole drugs in A. flavus. The study of the relationship between drug dosage and treatment duration with resistance and the reduction of fitness costs in resistant strains is a major perspective of this study. This work could help to establish recommendations for the treatment of infections with resistant strains of A. flavus.
Exogenous alpha‐lipoic acid treatments reduce the oxidative damage caused by drought stress in two grapevine rootstocks
Authors: Daler Selda , Kaya Ozkan 
Published: July 2024

AbstractDrought represents the predominant and most critical abiotic stress challenge within the domain of viticulture, necessitating the identification and application of efficacious strategies to ameliorate its deleterious effects. In the contemporary realm of abiotic stress management, the deployment of α‐lipoic acid (α‐Lipo), known for its antioxidant capabilities, as an exogenous treatment has been investigated for mitigating various abiotic stresses in numerous plant species, yet a detailed exploration of its efficacy in alleviating drought stress in grapevines remains to be conclusively determined. This study aimed to elucidate the adaptive mechanisms against drought stress by examining the effects of different α‐Lipo concentrations (0, 1, 25 and 50 μM) applied on the foliar under well‐irrigated and drought conditions on American grapevine rootstocks ‘1103 P' (drought tolerant) and ‘3309 C' (drought sensitive). Our findings revealed that the efficacy of α‐Lipo varied significantly depending on rootstock type and irrigation status. 1103 P rootstock treated with 1 μM α‐Lipo under well‐irrigated conditions showed greater positive effects on growth traits, photosynthetic and osmotic parameters. In contrast, in rootstock 3309 C under the same conditions, the highest effects were obtained at 25 and 50 μM α‐Lipo concentrations. Under drought stress conditions, 50 μM α‐Lipo treatment improved physiological parameters (chlorophyll content, proportional water coverage and stomatal conductance), proline content and antioxidant enzyme activities (SOD, CAT and APX), while reducing electrolyte leakage and MDA levels in both rootstocks, showing a strong potential to increase oxidative stress tolerance and sustain plant growth. Heatmap visualization analysis confirmed the data obtained from Principal Component Analysis (PCA) and revealed that 1103 P treated with 50 μM α‐Lipo under drought stress conditions exhibited superior physiological performance compared to 3309 C under the same conditions. This indicates the importance of potential rootstock differences in stress adaptation or α‐Lipo uptake efficiency. These findings suggest that α‐Lipo holds promise as an eco‐friendly, natural bio‐stimulant for use in arid environments, contributing to the advancement of sustainable agricultural practices in the foreseeable future.
Assessing genetic parameters for first parity reproductive traits for early selection in Saanen × Beetal goats of India
Authors: Sahoo Shweta , Alex Rani , Vohra Vikas , Mukherjee Sabyasachi , Gowane Gopal R. 
Published: July 2024

AbstractThe present study aimed to evaluate the genetic parameters of first parity reproductive traits. Information on 762 reproductive records on Saanen × Beetal (S × B) goats reared for approximately five decades was collected from ICAR‐National Dairy Research Institute, Karnal, Haryana (1973–2020). For genetic analysis, single‐trait and multiple‐trait animal models were used. Gibbs sampler for animal model (GSAM) approach was used for estimating (co)variance components of reproductive traits. Six different single‐trait animal models (with or without maternal and environmental effects) were used and the deviance information criterion (DIC) determined the best model. The least squares mean for age at first service (AFS), age at first kidding (AFK), service period (SP), dry period (DP), gestation length (GL), kidding interval (KI), litter weight (LW), number of kids born (NKB) and number of female kids born (NFKB) in first parity were 526.99 ± 4.86, 662.96 ± 5.03, 219.11 ± 6.25, 109.38 ± 6.00, 150.48 ± 0.27, 356.63 ± 4.80 days, 3.87 ± 0.05 kg, 1.27 ± 0.02 and 0.67 ± 0.03, respectively. Lower heritability estimates for these reproductive traits revealed a sparse scope for genetic improvement. Multivariate analysis using Model 1 was carried out to evaluate the genetic and phenotypic correlation of these nine reproductive traits. The genetic correlation of DP and SP was negatively with LW, NKB and NFKB, which is favourable as reduction in SP and DP can improve these economically important traits through indirect selection. Consistent efforts towards genetic improvement of these goat flock poses a promising future for meat industry owing to high prolificacy and good reproductive potential in this flock.
Specific microRNAs in stallion spermatozoa are potential biomarkers of high functionality
Authors: Ing Nancy H. , Konganti Kranti , Ghaffari Noushin , Johnson Charles D. , Forrest David W. , Love Charles C. , Varner Dickson D. 
Published: July 2024

AbstractMales of some species, from horses to humans, require medical help for subfertility problems. There is an urgent need for novel molecular assays that reflect spermatozoal function. In the last 25 years, studies examined RNAs in spermatozoa as a window into gene expression during their development and, more recently, for their functions in early embryo development. In clinics, more dense spermatozoa are isolated by density gradient centrifugation before use in artificial insemination to increase pregnancy rates. The objectives of the current study were to discover and quantify the microRNAs in stallion spermatozoa and identify those with differential expression levels in more dense versus less dense spermatozoa. First, spermatozoa from seven stallions were separated into more dense and less dense populations by density gradient centrifugation. Next, small RNAs were sequenced from each of the 14 RNA samples. We identified 287 different mature microRNAs within the 11,824,720 total mature miRNA reads from stallion spermatozoa. The most prevalent was miR‐10a/b‐5p. The less dense spermatozoa had fewer mature microRNAs and more microRNA precursor sequences than more dense spermatozoa, perhaps indicating that less dense spermatozoa are less mature. Two of the most prevalent microRNAs in more dense stallion spermatozoa were predicted to target mRNAs that encode proteins that accelerate mRNA decay. Nine microRNAs were more highly expressed in more dense spermatozoa. Three of those microRNAs were predicted to target mRNAs that encode proteins involved in protein decay. Both mRNA and protein decay are very active in late spermiogenesis but not in mature spermatozoa. The identified microRNAs may be part of the mechanism to shut down those processes. The microRNAs with greater expression in more dense spermatozoa may be useful biomarkers for spermatozoa with greater functional capabilities.
Optimal management of international reserves
Authors: Keungne Kouotang Léo‐Spencer , Ngoupeyou Armand Brice , Nji Fifen Ngangue Hussein 
Published: July 2024

AbstractThis article develops a continuous time stochastic model for determining the optimal international reserves management policy when the data generating process of international reserves is a geometric Brownian motion. The policy is a two‐parameter control‐limit that consists of an appropriate and a ceiling level on reserves holdings, given an exogenous floor on international reserves. The optimal solution is determined so as to minimize the total costs of international reserves holdings. It is proved that our results extend the framework of Frenkel and Jovanovic when the logarithm of international reserves is an arithmetic Brownian motion. We also explain that Jung paper does not extend Frenkel and Jovanovic model as claimed by the former. The model is calibrated to derive the optimal level and liquidity tranche size upper bound of international reserves of the CEMAC monetary union.
Strong heterologous electron sink outcompetes alternative electron transport pathways in photosynthesis
Authors: Hubáček Michal , Wey Laura T. , Kourist Robert , Malihan‐Yap Lenny , Nikkanen Lauri , Allahverdiyeva Yagut 
Published: July 2024

SUMMARYImprovement of photosynthesis requires a thorough understanding of electron partitioning under both natural and strong electron sink conditions. We applied a wide array of state‐of‐the‐art biophysical and biochemical techniques to thoroughly investigate the fate of photosynthetic electrons in the engineered cyanobacterium Synechocystis sp. PCC 6803, a blueprint for photosynthetic biotechnology, expressing the heterologous gene for ene‐reductase, YqjM. This recombinant enzyme catalyses the reduction of an exogenously added substrate into the desired product by utilising photosynthetically produced NAD(P)H, enabling whole‐cell biotransformation. Through coupling the biotransformation reaction with biophysical measurements, we demonstrated that the strong artificial electron sink, outcompetes the natural electron valves, the flavodiiron protein‐driven Mehler‐like reaction and cyclic electron transport. These results show that ferredoxin‐NAD(P)H‐oxidoreductase is the preferred route for delivering photosynthetic electrons from reduced ferredoxin and the cellular NADPH/NADP+ ratio as a key factor in orchestrating photosynthetic electron flux. These insights are crucial for understanding molecular mechanisms of photosynthetic electron transport and harnessing photosynthesis for sustainable bioproduction by engineering the cellular source/sink balance. Furthermore, we conclude that identifying the bioenergetic bottleneck of a heterologous electron sink is a crucial prerequisite for targeted engineering of photosynthetic biotransformation platforms.
Random Dynamic Responses of Two Parallel Interfacial Cracks Between a Functionally Graded Material Strip and Two Dissimilar Elastic Strips
Authors: Singh Ritika 
Published: July 2024

Abstract
An analytical approach is presented in this article for the random dynamic study of two parallel interfacial cracks in a functionally graded material (FGM) strip that is bonded between two distinct elastic strips. One of the parallel cracks is placed at the interface of the elastic strip I and the FGM strip, and another is at the interface of the FGM strip and elastic strip II. A stationary stochastic process of time is used to model the dynamic loadings that are applied to the crack faces. To find the solution, the FGM strip is split into a number of substrips, and using an average method, the material properties of each substrip are reduced to random variables. A fundamental problem is formulated to find the solution. The boundary conditions are reduced to a set of singular integral equations employing the Fourier sine, Fourier cosine, and Laplace transforms, which are solved by using the collocation method. Further, the analytical expressions of dynamic stress intensity factors (DSIFs) about the crack tips in the time domain are obtained with the help of the improved Dubner and Abate's method. Finally, the Monte Carlo method is used to obtain the mathematical expectation and standard deviation of DSIFs. The outcomes of this study are also verified. The unique aspect of this study is the pictorial illustration of mathematical expectation and standard deviation as functions of the number of substrips, functionally graded parameter, thickness of the strips, and length of parallel interfacial cracks.
Prediction of Oil Pipeline Process Operating Parameters Based on Mechanism and Data Mining
Authors: Wei Lixin , Wang Lan , Zhou Qiang , Gao Yuhang 
Published: July 2024

Abstract
Precisely forecasting the operational characteristics of oil pipelines is essential for developing rational design, production, and operation strategies, as well as reducing energy consumption and saving energy. Due to significant disparities in the computation outcomes of conventional mechanism models and the inadequate performance of machine learning models when handling limited sample data, their conclusions likewise lack tangible significance. In this study, a novel physics-guided neural network (PGNN) model, which integrates mechanisms with machine learning models, is introduced. The proposed model incorporates essential physical intermediate factors that impact the temperature and pressure of oil pipelines as artificial neurons within the loss function. Additionally, an adaptive moment estimate approach is employed to optimize the parameters of the model. Through a comparative analysis of various models' predictive capabilities on an oil pipeline, it was shown that PGNN has the highest level of accuracy in forecasting pipeline temperature and pressure. Furthermore, PGNN demonstrates the ability to generate satisfactory prediction outcomes even with a limited sample size. Simultaneously, the predictive outcomes of PGNN exhibit a stronger correlation with variables that have a direct impact on temperature and pressure.