bluuebunny/crossref_metadata_2025 huggingface dataset:
Low light reduces saffron corm yield by inhibiting starch synthesis
Authors: Yang Weijing , Li Xin , Chang Fei , Qiu Xue , Huang Xulong , Feng Zhan , Yan Jie , Wu Qinghua , Wen Feiyan , Pei Jin , Zhou Tao
Published: January 2025

The mechanisms by which low light modulates source-sink dynamics, affecting starch synthesis and formation of underground storage organs in geophyte, remain unclear. In this study, a two-year field experiment was conducted under natural light (NL) and low light (LL, 50% of NL intensity) conditions. LL resulted in a 23.66% and 21.23% reduction in corm yield in 2023 and 2024, respectively. Saffron plants under LL had larger, longer leaves with a higher proportion of dry weight (DW) compared to those under NL. Despite the marked inhibition of photosynthetic capacity, initial DW, sucrose and glucose concentrations in leaves were comparable to those under NL. Carbohydrate analysis revealed that starch concentration in the mother corms under LL decreased by 18.00% relative to NL, while sucrose and glucose concentrations increased by 28.44% and 68.44%, respectively. At the corm expansion stage, sucrose concentration in leaves and daughter corms under LL conditions was 17.32% and 54.08% higher than under NL, but glucose and starch concentrations in daughter corms were 22.08% and 10.22% lower, respectively. Additionally, the activity of invertase (INV), sucrose synthase in the decomposition direction (SUS) and ADP-glucose pyrophosphorylase (AGPase) in daughter corms were reduced under LL. LL also affected phytohormones concentrations, with increased levels of indole-3-acetic acid (IAA) and gibberellin (GA1) in LL leaves and daughter corms, and decreased abscisic acid (ABA) levels. Transcriptome and quantitative PCR analyses showed that LL upregulated the expression of genes involved in glycolysis and the tricarboxylic acid cycle in leaves, while downregulating CsSUS, CsINV1, CsAGPS1, CsZEP, and CsNCED, which are key to sucrose hydrolysis, starch synthesis, and ABA biosynthesis. Exogenous GA3 application further inhibited SUS, INV and AGPase activities in daughter corms, indicating that high GA concentrations impair carbohydrate metabolism in these organs. In conclusion, LL decreases saffron corm yield by promoting the allocation of reserves from mother corms to leaves at the seedling stage. By the period of the daughter corms enlargement, elevated GA1 and IAA levels and reduced ABA concentration promote leaf growth while inhibiting carbohydrate metabolism in daughter corms, thereby reducing sucrose transport from leaves to daughter corms and suppressing corm yield formation.
The key metabolic genes and networks regulating the fruit acidity and flavonoid of Prunus mume revealed via transcriptomic and metabolomic analyses
Authors: Gao Xuan , Wu Shuangshuang , Lv Guosheng , Wang Mengyang , Li Lingxiang , Liu Yahui , He Feng , Xiao Jiaxin
Published: January 2025

The acidic taste of Mei fruit (Prunus mume) is a major contributor to its quality, but its formation mechanism remains unclear. Here, we unraveled the networks of organic acid and flavonoid metabolism in two Mei fruit. The results showed that the differentially expressed genes were mainly concentrated in the processes of carbohydrate derivative binding, carboxylic acid, and organic acid metabolism. While the differentially accumulated metabolites were mainly associated with flavone and flavonol biosynthesis and amino acid and carbon metabolism. Moreover, we identified key metabolites, such as citric and succinic acids, which may be central to the development of acidity in Mei fruit, and determined that they are under the regulatory influence of specific genes, including galactinol-sucrose-galactosyltransferase 5, mitogen-activated protein kinase kinase kinase NPK1-like, glutamate receptor, and chalcone isomerase. Furthermore, transcription factors ERF027, bHLH92, bHLH35, and WRKY23 were identified as potential pivotal regulators within these networks. These results provide new insights into the metabolic regulation of acidity and flavonoid in Mei fruit.
The limits of restrictions on free competition in the state of emergency—the Hungarian fuel and food retail price maximisation in the light of the Hungarian constitutional court’s, the Strasbourg court’s and the Luxembourg court’s jurisprudence
Authors: Erdős Csaba , Verebélyi Viktória , Knapp László
Published: January 2025

Since March 2020, Hungary has almost continuously been under a type of special legal order, the state of emergency, which was first introduced to better protect against the COVID-19 epidemic and then in May 2022—following the amendment of the Fundamental Law—due to the Russian-Ukrainian war. Both the crises caused by the epidemic and the armed conflict in the neighbouring country were de facto limited not only to the health and migration-humanitarian fields, but the Government made use of the exceptional legislative powers of the special legal order in almost all areas of life. Economic regulation was no exception: in 2021, the Government capped the retail price of fuel, and from February 2022 onwards, the retail price of several basic foodstuffs (including flour, sugar, milk, chicken breast and other meats, and later eggs and potatoes). The aim of this paper is to show the limits of one of the most powerful state interventions in the economy: the price maximisation. This can basically be determined on the basis of the relevant case law of three fora of legal protection—the Hungarian Constitutional Court, the European Court of Human Rights in Strasbourg and the Court of Justice of the European Union. A comparison of the case law of the above-mentioned three courts also shows which legal protection mechanism is most effective against legislation restricting the free competition—at least in a period of special legal order.
Compositional depths of cognitive semantics: bridging perceptual experiences and conceptual structures
Authors: Pala Kiran , Nedumpozhimana Vasudevan , Shalu S.
Published: January 2025

The primary aim of this research was to investigate the intricate relationship between the structural elements of experiences and their essential role in meaning formation. The analysis focused on understanding the nature of mental representations and the subjective, phenomenal qualities that emerge within experiences. To achieve this, an integrated approach, combining cognitive semantics with phenomenological analysis, was employed to examine the compositional complexities of the dynamic interaction between a priori and immediate experiences and their significance in meaning formation. The study highlights the interconnectivity of structural elements within experience as a critical factor in shaping the phenomenal qualities of mental representations. Another key contribution of this study is the introduction of the “fulfiller” concept, which underscores the importance of absent qualities in meaning formation-an often-overlooked aspect in traditional models that focus solely on present attributes. The “fulfiller” concept emphasizes how absence, in addition to presence, influences meaning assignment. This inclusion enhances our understanding of meaning formation by considering both the tangible and intangible dimensions of the experiential-intentional process, offering a more comprehensive framework for understanding how meaning emerges from the complex interaction of present and absent qualities.
Studying engagement in educational settings: a mapping review on high-impact academic engagement research
Authors: Loyola-Carrillo Paola , Vega-Muñoz Alejandro , Salazar-Sepúlveda Guido , Gil-Marín Miseldra , Adsuar-Sala José
Published: January 2025

Introduction

Academic engagement provides opportunities and resources for students to engage in socio-educational interactions and learning. Our study provides an overview of high-impact research in academic engagement and the potential causes of its high valuation in the scientific community.

Methods

We conducted a mapping review using bibliometric analysis of 1,607 articles indexed in Web of Science, processed mainly by VOSviewer software.

Results

The publication of selected articles grew exponentially year by year, presenting concentration levels of 1% in authorship, 49% in a single country, and 5% in journals, identified as outstanding Keywords plus® central aspects of academic engagement (classroom-social environment and school engagement), in addition, 6% were in highly cited articles.

Conclusion

These highly cited articles (6%) are associated with authors with high levels of publication. The most cited current topics relate to the motivation and emotional aspects of academic engagement.
The curvilinear relationship between Framingham Steatosis Index and depression: insights from a nationwide study
Authors: Jiang Chunqi , Wang Bo , Wang Ning , Wang Jun , Qu Yinuo , Zhao Guang , Zhang Xin
Published: January 2025

Background

The Framingham Steatosis Index (FSI) serves as a diagnostic metric for fatty liver. While research has established a link between depression and fatty liver, the association with the Framingham Steatosis Index (FSI) remains undocumented. The aim of this study is to explore the potential correlation between FSI and depression, addressing this research void.

Methods

Our data originates from the National Health and Nutrition Examination Survey (NHANES) database. We employed the PHQ-9 questionnaire for the evaluation of depressive symptoms. We investigated the association between FSI and depression using a weighted multiple logistic regression model and stratified analysis. Non-linear associations were explored using fitted smooth curves. A recursive method was employed to identify inflection points. Subgroup analyses were conducted to examine differences in the association between FSI and depression within subgroups.

Results

Our research encompassed a total of 19,697 participants. Multivariate logistic regression analysis, adjusted for potential confounding factors, demonstrated a significant positive association between FSI and depression, with OR of 1.14 (95% CI: 1.10, 1.18). Stratified analysis indicated that a significant positive correlation exists between FSI and depression among all groups except those with BMI below 30. The non-linear relationship was further confirmed by the restricted cubic splines analysis, which revealed an inflection point at an FSI value of 29.72. Below this threshold, there was no significant correlation, while above it, a positive correlation was observed. Subgroup analysis revealed statistically significant interactions between FSI and depression within the educational attainment groups.

Conclusion

Our study’s discovery is the curvilinear relationship between FSI and depression. Factors such as inflammation, hormonal levels, and metabolic disruptions could be the underlying mechanisms driving this relationship. This finding offers valuable insights that could inform the development of comprehensive intervention strategies for managing depression in clinical settings.
Pilot of a team-based quality improvement strategy to improve cardiovascular risk factors care in community mental health centers
Authors: Murphy Karly A. , Gennusa Joseph , Dalcin Arlene T. , Cook Courtney , Goldsholl Stacy , Fink Tyler , Daumit Gail L. , Wang Nae-Yuh , Thompson David , McGinty Emma E.
Published: January 2025

Introduction

Populations with serious mental illness are less likely to receive evidence-based care for cardiovascular disease (CVD) risk factors. We sought to characterize the implementation of an adapted team-based quality improvement strategy to improve mental health providers’ delivery of evidence-based CVD risk factor care.

Methods

In a 12-month, single arm pre/post pilot study in four behavioral health homes embedded within psychiatric rehabilitation programs, sites implemented an adapted Comprehensive Unit Safety Program (CUSP). Primary measures examined changes in organizational quality improvement culture and provider self-efficacy for CVD risk factor care. Secondary measures examined changes in acceptability, appropriateness, and feasibility of CUSP and receipt of guideline-concordant care for hypertension, dyslipidemia, and diabetes.

Results

Provider self-efficacy to coordinate care for hypertension and diabetes improved, but organizational quality improvement culture did not change. Acceptability, appropriateness, and feasibility were rated highly but did not change pre/post CUSP. The percentage who reached goals per national guidelines improved for those with dyslipidemia but not for those with hypertension or diabetes. CUSP teams implemented processes to build staff capacity, standardize communication, elicit feedback, and deliver education on coordination for CVD risk factors.

Conclusion

This pilot study showed no effects of CUSP on organizational quality improvement culture or provider self-efficacy, the mechanisms by which CUSP is expected to improve care processes. Long term investments are needed to support organizational quality improvement work and providers’ efficacy to delivery - evidence-based CVD risk factor care delivery.

Clinical Trial Registration

http://www.ClinicalTrials.gov, identifier NCT04696653.
Effect and prediction of long-term weather and pollutant exposure on hemorrhagic fever with renal syndrome: based on statistical models
Authors: Hou Weiming
Published: January 2025

Background

Previous studies have typically explored daily lagged relationships between hemorrhagic fever with renal syndrome (HFRS) and meteorology, with a limited seasonal exploration of monthly lagged relationships, interactions, and the role of pollutants in multiple predictions of hemorrhagic fever.

Methods

Our researchers collected data on HFRS cases from 2005 to 2018 and meteorological and contaminative factors from 2015 to 2018 for the northeastern region. First, we applied the moving epidemic method (MEM) to estimate the epidemic threshold and intensity level. Then, we used a distributed lag non-linear model (DLNM) and a generalized additive model (GAM) with a maximum lag of 6 months to evaluate the lagged and interaction effects of meteorological and pollution factors on the HFRS cases. Multiple machine learning models were then applied after Spearman’s rank correlation coefficient analysis was performed to screen for environmental factors in the Northeastern region.

Results

There was a yearly downward trend in the incidence of HFRS in the northeastern region. High prevalence threshold years occurred from 2005 to 2007 and from 2012 to 2014, and the epidemic months were mainly concentrated in November. During the low prevalence threshold period, the main lag factor was low wind direction. In addition, the meteorological lag effect was pronounced during the high prevalence threshold period, where the main lag factors were cold air and hot dew point. Low levels of the AQI and PM10 and high levels of PM2.5 showed a dangerous lag effect on the onset of HFRS, while extremely high levels of PM2.5 appeared to have a protective effect. High levels of the AQI and PM10, as well as low levels of PM2.5, showed a protective lag effect. The model of PM2.5 and the AQI interaction pollution is better. The support vector machine (SVM)-radial algorithm outperformed other algorithms when pollutants are used as predictor variables.

Conclusion

This is the first mathematically based study of the seasonal threshold of HFRS in northeastern China, allowing for accurate estimation of the epidemic level. Our findings suggest that long-term exposure to air pollution is a risk factor for HFRS. Therefore, we should focus on monitoring pollutants in cold conditions and developing HFRS prediction models.
The potential of genomic epidemiology: capitalizing on its practical use for impact in the healthcare setting
Authors: Pacchiarini Nicole , McKerr Caoimhe , Morgan Mari , Connor Thomas R. , Williams Christopher
Published: January 2025

The rapid detection and containment of healthcare-associated infections (HCAIs) is critical in preventing and controlling infectious disease outbreaks within healthcare settings. Whole genome sequencing (WGS) has emerged as a powerful tool for tracking the transmission dynamics of pathogens and when used alongside traditional epidemiological methods it can better inform our understanding of the pathogen origin, pathway and extent of transmission. Additionally, WGS can aid in identifying previously unrecognized reservoirs of infection, allowing for more effective control strategies and targeted interventions. This article describes the incorporation of WGS into infectious disease management in Wales and explores it in the context of COVID-19 and Clostridioides difficile. We also describe the developments made to the workforce in Wales to enable the expansion of WGS and reflect on the resources, infrastructure and training frameworks still required.
An extreme value analysis of daily new cases of COVID-19 in Africa
Authors: Nadarajah Saralees , Umar Adamu Abubakar
Published: January 2025

Modeling COVID-19 cases in Africa is crucial for developing effective public health strategies, allocating resources efficiently, and mitigating the impact of the pandemic on vulnerable populations. A recent paper by the first author provided an extreme value analysis of daily new cases of COVID-19 from sixteen countries in west Africa. In this paper, we broaden our analysis to encompass data spanning all fifty four African nations over a period of forty four months. We identified extreme values as the monthly maximums of daily new cases. Utilizing the generalized extreme value distribution, we fitted the data, allowing two of its three parameters to vary linearly or quadratically in relation to the month number. Twenty six countries demonstrated significant downward trends in monthly maximums. Two countries demonstrated significant upward trends in monthly maximums. Nineteen countries demonstrated significant quadratic trends where monthly maximums initially increased before decreasing. The sharpest and weakest of the downward trends with respect to location were for Mali and Liberia, respectively. The sharpest and weakest of the downward trends with respect to scale were for Egypt and Libya, respectively. Recommendations are given for each country. We evaluated the adequacy of fits through probability plots and the Kolmogorov-Smirnov test. Subsequently, the fitted models were employed to determine quantiles of the monthly maximum of new cases, as well as their limits extrapolated to infinite month numbers.
Is synthetic data generation effective in maintaining clinical biomarkers? Investigating diffusion models across diverse imaging modalities
Authors: Hosseini Abdullah , Serag Ahmed
Published: January 2025

Introduction

The integration of recent technologies in medical imaging has become a cornerstone of modern healthcare, facilitating detailed analysis of internal anatomy and pathology. Traditional methods, however, often grapple with data-sharing restrictions due to privacy concerns. Emerging techniques in artificial intelligence offer innovative solutions to overcome these constraints, with synthetic data generation enabling the creation of realistic medical imaging datasets, but the preservation of critical hidden medical biomarkers is an open question.

Methods

This study employs state-of-the-art Denoising Diffusion Probabilistic Models integrated with a Swin-transformer-based network to generate synthetic medical data. Three distinct areas of medical imaging - radiology, ophthalmology, and histopathology - are explored. The quality of synthetic images is evaluated through a classifier trained to identify the preservation of medical biomarkers.

Results

The diffusion model effectively preserves key medical features, such as lung markings and retinal abnormalities, producing synthetic images closely resembling real data. Classifier performance demonstrates the reliability of synthetic data for downstream tasks, with F1 and AUC reaching 0.8–0.99.

Discussion

This work provides valuable insights into the potential of diffusion-based models for generating realistic, biomarker-preserving synthetic images across various medical imaging modalities. These findings highlight the potential of synthetic data to address challenges such as data scarcity and privacy concerns in clinical practice, research, and education.
Artificial intelligence applied to diabetes complications: a bibliometric analysis
Authors: Tao Yukun , Hou Jinzheng , Zhou Guangxin , Zhang Da
Published: January 2025

Background and aims

Artificial intelligence (AI)-driven medical assistive technology has been widely used in the diagnosis, treatment and prognosis of diabetes complications. Here we conduct a bibliometric analysis of scientific articles in the field of AI in diabetes complications to explore current research trends and cutting-edge hotspots.

Methodology

On April 20, 2024, we collected and screened relevant articles published from 1988 to 2024 from PubMed. Based on bibliometric tools such as CiteSpace, Vosviewer and bibliometix, we construct knowledge maps to visualize literature information, including annual scientific production, authors, countries, institutions, journals, keywords and research hotspots.

Results

A total of 935 articles meeting the criteria were collected and analyzed. The number of annual publications showed an upward trend. Raman, Rajiv published the most articles, and Webster, Dale R had the highest collaboration frequency. The United States, China, and India were the most productive countries. Scientific Reports was the journal with the most publications. The three most frequent diabetes complications were diabetic retinopathy, diabetic nephropathy, and diabetic foot. Machine learning, diabetic retinopathy, screening, deep learning, and diabetic foot are still being researched in 2024.

Conclusion

Global AI research on diabetes complications is expected to increase further. The investigation of AI in diabetic retinopathy and diabetic foot will be the focus of research in the future.
Influence of working conditions on German paramedics' intention to leave the profession: a cross-sectional study
Authors: Hofmann Thomas , Stanley Michael , Möckel Luis
Published: January 2025

Introduction

It is well known that Germany's ambulance service (AS) suffers from a shortage of qualified personnel, which may increase in the following years. For this reason, this study aimed to determine the percentage of AS staff considering leaving their profession and to analyse the possible causes.

Methods

A self-developed questionnaire and the Employee Experience Questionnaire (EXQ) were used for this cross-sectional study.

Results

A total of 814 AS staff with a mean age of 35.71 [standard deviation (SD) 9.78] years were included in this study. Immediately leaving the AS was the intention of 17.27% of participants, with 2.86% having already resigned, 14.29% taking actions such as applying for a job, and another 14.04% specifically planning to leave the AS in the foreseeable future. Those who plan to leave the AS immediately [3.82 (SD 0.79)] showed significantly lower EXQ scores than the group who plan to stay in the EMS until retirement [4.92 (SD 0.87); pTukey ≤0.001]. At the same time, it is noticeable that EMS staff often suffer from unfavourable working conditions, such as not being granted breaks, work-related calls during free time, and over time, and significant correlations with the planned length of stay in the paramedic service and exit thoughts were identified here.

Conclusion

Unfavourable working conditions further aggravate the already existing shortage of qualified personnel in the ambulance service, so measures by various decision-makers are imperative.
MicroRNA functions in osteogenic differentiation of periodontal ligament stem cells: a scoping review
Authors: Limlawan Pirawish , Vacharaksa Anjalee
Published: January 2025

This scoping review aimed to describe the differential microRNA (miRNA) functions in osteogenic differentiation of periodontal ligament stem cells (PDLSCs), and then analyze the potential of applying PDLSCs and miRNAs in bone regeneration. The databases of PubMed, Google Scholar and EBSCO search were performed by the 4 themes, including periodontal ligament stem cells, miRNA, osteogenic differentiation, and tissue regeneration. The original articles described miRNA functions in osteogenic differentiation of PDLSCs were identified and selected for content analyze. The articles suggested that PDLSCs have high potential in bone regeneration because of their multipotency and immunomodulation. PDLSCs are conveniently accessible and obtained from extracted teeth. However, recent evidence reported that PDLSCs of various origins demonstrate differential characteristics of osteogenic differentiation. Exosomal miRNAs of PDLSCs demonstrate a regulatory role in tissue regeneration. The properties of PDLSCs associated to miRNA functions are altered in differential microenvironmental conditions such as infection, inflammation, high-glucose environment, or mechanical force. Therefore, these factors must be considered when inflamed PDLSCs are used for tissue regeneration. The results suggested inflammation-free PDLSCs harvested from the middle third of root surface provide the best osteogenic potential. Alternatively, the addition of miRNA as a bioactive molecule also increases the success of PDLSCs therapy to enhance their osteogenic differentiation. In conclusion, Exosome-derived miRNAs play a key role in PDLSCs osteogenic differentiation during tissue regeneration. While the success of PDLSCs in tissue regeneration could be uncertain by many factors, the use of miRNAs as an adjunct is beneficial for new bone regeneration.
AI-powered estimation of tree covered area and number of trees over the Mediterranean island of Cyprus
Authors: Zenonos Anna , Li Sizhuo , Brandt Martin , Sciare Jean , Ciais Philippe
Published: January 2025

Trees play a crucial role in mitigating climate change by absorbing CO2 and providing biophysical cooling. The European Commission’s climate policies underscore the importance of forest monitoring systems to achieve substantial greenhouse gas reductions by 2030. In Cyprus, an EU member state located in the Eastern Mediterranean, and a climate change hot-spot, increasingly impacted by forest fires and more arid conditions, the absence of a comprehensive tree monitoring system hinders effective carbon stock assessment and land-based mitigation strategies. The exact tree population inside and outside forests is currently unknown. Artificial Intelligence is a powerful tool that can enable the development of tree monitoring systems by applying machine learning models to high-resolution image data. This study presents a deep learning neural network model applied to high resolution (10 cm) airborne images collected during the year 2019, to generate segmented tree crowns and the number of individual trees over selected areas of Cyprus, including a large national forest park, a forest park in the capital city, and a small urban area, encompassing a total studied area of 107km2. The model, previously applied in Denmark and Finland was completely re-tuned using local annotations to account for Cyprus’s specific conditions and achieved an overall accuracy of 90% and 93% to estimate the area covered by tree crowns and the number of trees, respectively. The results are regressed against coarser resolution tree cover maps to predict the area covered by tree crowns at a national level. The accuracy of the tree cover maps created by this study is compared to those of existing global tree cover maps, such as the Copernicus products. This work lays the foundation for establishing a tree-level inventory for Cyprus using airborne remote-sensing.
Exploring space: ethical dilemmas for catholicism
Authors: Balistreri Maurizio
Published: January 2025

This article explores the Catholic Church’s perspective on space exploration and construction of human settlements beyond Earth, highlighting the significant moral dilemmas posed by these endeavors. While the Church generally supports space exploration, biotechnologies such as genome editing, assisted reproduction, and artificial wombs – technologies potentially essential for human survival and reproduction in space – clash with its moral principles. Non-therapeutic genetic modifications, regarded by the Church as an arbitrary redesign of human nature, are categorically prohibited. Similarly, assisted reproduction is considered morally unacceptable due to the destruction of embryos, the separation of the unitive and procreative aspects of human sexuality, and it fosters the selection of embryos and eugenics practices. Although the use of artificial wombs offers practical and safety benefits in space, it is also incompatible with the Church’s teachings on the dignity of human life and procreation. These conflicts underscore the Church’s challenge in reconciling humanity’s aspirations for space exploration with its ethical and spiritual framework. If technologies that fundamentally alter human nature or reproduction are excluded, the prospect of human expansion into space may remain morally unattainable.
Within-individual design for assessing true individual responses in resistance training-induced muscle hypertrophy
Authors: Chaves Talisson Santos , da Silva Deivid Gomes , Lixandrão Manoel Emílio , Libardi Cleiton Augusto
Published: January 2025

Understanding interindividual variability in muscle hypertrophy in response to resistance training (RT) is a key focus of contemporary research. Common aims include identifying determinants of variability and recognizing individuals who do not respond to RT (i.e., non-responders). However, accurately identifying true individual responses (TIR) remains challenging due to the complex nature of muscle hypertrophy assessments. This complexity arises from distinguishing the TIR from natural variation in muscle mass over time and random measurement error in pre- and postintervention assessments. Existing studies have often overlooked this complexity, failing to employ experimental designs capable of isolating the TIR. Additionally, the reliance on random measurement error assessments based on group level data may not adequately capture the biological variation in muscle mass within individuals. In this context, we propose an experimental design based on unilateral, within-subject resistance training, capable of estimating biological variation in muscle mass and identifying TIR to RT-induced muscle hypertrophy. Additionally, we present an approach to effectively identify non-responders.
Factores asociados al éxito en el otorgamiento de las patentes y el impacto comercial en universidades reconocidas como innovadoras a nivel global
Authors: Quiroga-Arcieniegas Vanessa-Mercedes
Published: January 2025

Uno de los aspectos relevantes al trabajar datos de innovación son sus múltiples definiciones, sin embargo, la OCDE en el Manual de Oslo estableció que una innovación sí y sólo sí era una innovación cuando esta pasaba por una validación de mercado. El propósito de este trabajo fue encontrar los determinantes que expliquen la innovación de algunas de las principales universidades del mundo, medida a través del licenciamiento de las patentes. Se realizó un modelo de regresión lineal múltiple que tuvo en cuenta las variables internas que afectan a las universidades. Se aplicó un muestreo no probabilístico por conveniencia utilizando como variables dependientes: el indicador de impacto comercial de las patentes y la tasa de éxito de las patentes publicados por el ranking de Reuters. En cuanto a las variables independientes, se utilizaron algunos de los indicadores del ranking Times Higher Education (THE).  Los resultados de los modelos econométricos encontraron que los ingresos provenientes de la industria y el nivel de la investigación de las universidades afectan de manera significativa el éxito en el otorgamiento de las patentes y su impacto comercial en las universidades estudiadas. Concluyendo que, si las universidades quieren contribuir cada vez más a la innovación en los países donde operan desde la perspectiva de las patentes, es necesario que estrechen lazos de cooperación con la industria o sector productivo con el propósito de satisfacer cada vez más necesidades de la sociedad basada en conocimiento y desarrollo tecnológico.
Influencia de la técnica del aprendizaje basado en proyectos en el desarrollo de la expresión oral
Authors: Méndez-Fernández Bertha Rosario , González-Cabrera Johanna Karina
Published: January 2025

El Aprendizaje Basado en Proyectos (ABP) es una de las metodologías que impulsa la participación activa de los estudiantes en el aprendizaje, favorece el desarrollo de destrezas lingüísticas, fomenta el uso de recursos y estrategias, mejora el rendimiento académico y promueve la motivación y la confianza; además, el ABP puede sustituir a la enseñanza tradicional de una forma muy efectiva, debido a que cambia el rol del docente y el estudiante; en ese contexto el presente artículo tuvo por objetivo analizar los resultados de la intervención del Aprendizaje Basado en Proyectos enfocado en el periodismo escolar para mejorar la expresión oral de los estudiantes de Tercero de Bachillerato. Este estudio empleó un diseño preexperimental preprueba y posprueba, para evaluar la eficacia de una intervención educativa con una duración de 12 semanas, se evaluó en términos de mejora en siete aspectos clave de la expresión oral: habla, vocabulario, volumen, comprensión, postura del cuerpo y contacto visual y contenido. Se compararon los resultados pre y post intervención mediante pruebas de Wilcoxon, mostrando mejoras significativas en todas las áreas, resaltando de esta manera el impacto positivo que ha tenido esta estrategia metodológica en el desarrollo de las habilidades lingüísticas de los estudiantes, lo cual sirve de referente para futuras investigaciones.
Comunicación organizacional interna y su influencia en el apoyo social percibido en clínicas privadas de Santa Elena
Authors: Villón-Laínez Shirley Melissa , Guerrero-Bejarano Maria Auxiliadora , Manosalvas-Vaca Carlos Aníbal
Published: January 2025

El presente estudio examina la incidencia de la comunicación organizacional interna en el apoyo organizacional percibido (AOP) en clínicas privadas de la provincia de Santa Elena. Su objetivo fue evaluar cómo una comunicación interna efectiva impacta en el apoyo social percibido por los trabajadores en el ámbito de la salud, particularmente tras la pandemia de COVID-19, periodo en el que se evidenciaron cambios en los ambientes organizacionales. A través de un enfoque cuantitativo con alcance descriptivo y explicativo, el estudio empleó cuestionarios estructurados en escala de Likert y validados previamente para medir la percepción de los empleados sobre la claridad, accesibilidad y confiabilidad de la comunicación interna. Los resultados revelan que una comunicación organizacional estructurada y accesible incrementa significativamente la percepción de apoyo entre los colaboradores, fortaleciendo así un ambiente laboral más cohesivo y productivo. Este trabajo contribuye al diseño de estrategias orientadas a optimizar las relaciones laborales y mejorar el clima organizacional en instituciones de salud, identificando áreas críticas en las que la comunicación interna y el apoyo organizacional. Se concluyó que una comunicación interna eficaz no solo facilita la transmisión de objetivos y valores corporativos, sino que influye directamente en la satisfacción y lealtad de los empleados hacia la organización; lo que resulta fundamental para alcanzar niveles óptimos de desempeño y estabilidad en el personal, aspectos esenciales en la gestión de recursos humanos en el sector salud.
Advantages of Density in Tensor Network Geometries for Gradient-Based Training
Authors: Masot-Llima Sergi , Garcia-Saez Artur
Published: January 2025

Tensor networks are a very powerful data structure tool originating from simulations of quantum systems. In recent years, they have seen increased use in machine learning, mostly in trainings with gradient-based techniques, due to their flexibility and performance achieved by exploiting hardware acceleration. As ansatzes, tensor networks can be used with flexible geometries, and it is known that for highly regular ones, their dimensionality has a large impact on performance and representation power. For heterogeneous structures, however, these effects are not completely characterized. In this article, we train tensor networks with different geometries to encode a random quantum state, and see that densely connected structures achieve better infidelities than more sparse structures, with higher success rates and less time. Additionally, we give some general insight on how to improve the memory requirements of these sparse structures and the impact of such improvement on the trainings. Finally, as we use HPC resources for the calculations, we discuss the requirements for this approach and showcase performance improvements with GPU acceleration on a last-generation supercomputer.
Impact of the Application of Rhizobacteria in Bean Cultivars: Potential for Sustainable Management
Authors: Silva Guilherme Romão , Teixeira Itamar Rosa , Ferreira Alexandre Braz , da Silva Gisele Carneiro , Rocha Ednaldo Cândido , Santos Fenelon Lourenço Sousa , Neto Maurilio Rosa Benício , Cunha Nathan Mickael de Bessa , Casaroli Derblai
Published: January 2025

The use of bacterial inoculants has great potential to improve yield and sustainability; however, application forms still face bottlenecks, such as the standardization of methods and compatibility with different varieties of bean. The objective of this study was to evaluate the growth and yield of bean cultivars subjected to inoculation and co-inoculation with rhizobacteria. The experiments were carried out using a randomized block design, with three replicates. Treatments consisted of four bean cvs. (BRS FC 402, BRS Estilo, BRS Pitanga, and BRS Esteio), subjected to inoculation with Rhizobium and co-inoculation with Azospirillum, applied to seed or soil, plus eight additional treatments with a mineral N source and its absence (control) for each cvs. The use of co-inoculation of R. tropici with A. brasilense promoted an improvement in the morphophysiological and agronomic characteristics, attributed to the ability of rhizobial bacteria to supply nitrogen to plants and to Azospirillum through hormonal action. The cvs. BRS Estilo and BRS Esteio had the best grain yields when co-inoculated via soil, 2049 and 1831 kg ha−1, respectively. Co-inoculation with R. tropici + A. brasilense applied to the soil can be used as an exclusive source of N supply in the bean, contributing to lower costs and more sustainable production.
Impact of Deficit Drip Irrigation with Brackish Water on Soil Water–Salt Dynamics and Maize Yield in Film-Mulched Fields
Authors: Guo Tongkai , Huang Xi , Feng Kewei , Mao Xiaomin
Published: January 2025

Maize production in the arid and semi-arid regions of northwest China is limited by water scarcity, while the abundance of brackish water highlights the opportunity for its effective and sustainable utilization. A 2-year field experiment (2022–2023) was conducted in the Shiyang River Basin to investigate the impacts of deficit irrigation with brackish water on soil moisture, salinity, temperature, crop growth index, yield, and water productivity. Six treatments were implemented, consisting of two irrigation levels (W1: 75%I, W2: 100%I) and three water quality gradients (S0: 0.7 g L−1, S1: 3.7 g L−1, S2: 5.7 g L−1 in 2022 and 7.7 g L−1 in 2023). Results indicated that brackish irrigation (except S0) increased soil salinity, keeping the soil water storage at higher levels, while decreased maize yield, and water productivity (WP). Compared with full irrigation at the same salinity level, deficit irrigation decreased soil salinity, keeping the soil water storage at lower levels, while increasing soil temperature, which led to lower maize yield but resulted in higher WP. Path analysis of soil hydrothermal salinity and crop growth indicators demonstrated that soil salinity changes play a crucial role in determining maize plant height and yield. S0W2 (100% irrigation, 0.7 g L−1) achieved the highest maize yield, with S0W1 yielding 5.15% less. However, the water productivity (WP) of S0W1 was 17.66% higher than that of S0W2. Therefore, considering the combined factors of maize yield, water productivity, and water-saving benefits, the use of S0W1 (75% irrigation, 0.7 g L−1) is recommended.
Enhancing Nutritional and Functional Properties of Broccoli Leaves Through Selenium Biofortification: Potential for Sustainable Agriculture and Bioactive Compound Valorization
Authors: Buttarelli Melina Soledad , Céccoli Gabriel , Trod Betiana Soledad , Stoffel María Micaela , Simonutti Marianela , Bouzo Carlos Alberto , Turowski Valeria Rosana , Perez Adrián Alejandro , Llugany Mercè , Sánchez-Martín María-Jesús , Daurelio Lucas Damián , Guevara María Gabriela , Muñoz Fernando Felipe
Published: January 2025

Selenium (Se) biofortification is a promising agronomic strategy to enhance the dietary intake of this essential micronutrient while simultaneously adding value to agricultural by-products like Brassica oleracea L. var. italica leaves. This study evaluated the effects of foliar Se biofortification on a fresh market broccoli cultivar (‘Belstar’) using selenite and selenate (1 and 2 mM). Growth performance, biochemical properties, nutraceutical quality, and phytohormone profiles of broccoli leaves were analyzed, highlighting their potential as functional by-products. Multivariate analysis revealed that 2 mM selenite application was the most effective treatment, significantly improving several parameters. Selenium biofortification with 2 mM selenite increased essential nutrient content, including Se, Ca, S, Fe, Mn, Mg, and Mo. It also enhanced the soluble protein content (+2.2-fold), phenolic compounds (+1.5-fold), and total antioxidant capacity (+1.4-fold) compared to control plants. In this sense, the nutraceutical quality of broccoli leaves was markedly improved, supporting their use as a source of bioactive ingredients. Additionally, to assess practical applications, water-extracted Se-enriched broccoli leaves demonstrated antifungal activity against the plant pathogen Fusarium solani, attributed to Se-induced alterations in phytohormone profiles. These findings suggest that Se-biofortified broccoli leaves can serve as a sustainable source of essential nutrients and bioactive compounds for the food industry. Furthermore, their antifungal properties position them as potential eco-friendly biopesticides to combat plant pathogenic fungi, thereby promoting sustainable agriculture.
Exploring the Impact of Land Cover on the Occurrence of Ornithobacteriosis and Fowl Cholera: A Case-Case Study
Authors: Ouyang Lingyu , Campler Magnus R. , Wong Sandy , Xiao Ningchuan , Arruda Andréia G.
Published: January 2025

Ornithobacterium rhinotrachealis (ORT) and Pasteurella multocida (PM) are two major bacterial pathogens affecting the United States (US) commercial turkey industry. This retrospective observational case-case study aimed to investigate the association between land cover and confirmed disease occurrences attributed to PM or ORT in commercial turkey sites located in the Midwestern US A total of 65 farms from one poultry production company were included, where 28 had PM disease occurrences and 37 had ORT disease occurrences between 2014 and 2021. Risk factors of interest included land cover types (wetlands, forest, urban, pasture, herbaceous, barren, shrub), poultry-farm density in the area, and season and year of confirmed outbreak(s). A multivariable logistic regression model revealed that for every 1 m increase in distance from a farm to the nearest wetland, the odds of a confirmed disease occurrence related to PM decreased by approximately 0.24% compared to an ORT-related disease occurrence (p = 0.004). Meanwhile, PM occurrence during 2014–2017 was 98.5% higher than 2018–2019 and 93.2% higher than in 2020–2021. Broadly, the findings contribute to the dearth of research on land cover and turkey respiratory diseases and demonstrate that land cover is an important consideration for farm management and future study.
Lineage Diversification and Population Dynamics of the Qinghai Toad-Headed Agama (Phrynocephalus vlangalii) on the Qinghai–Tibet Plateau, with Particular Attention to the Northern Slope of the Kunlun–Arjin Mountains
Authors: Xu Rui , Song Qi , Chen Dali , Guo Xianguang
Published: January 2025

The Kunlun, Arjin, and Qilian mountain ranges mark the northern edge of the Qinghai–Tibet Plateau (QTP), where rapid uplift and Quaternary glacial cycles have shaped a unique cold desert ecosystem and species distribution. Despite sampling challenges, phylogeographic studies are crucial for understanding reptile populations such as the Qinghai toad-headed agama (Phrynocephalus vlangalii), a viviparous lizard with limited dispersal and multiple subspecies in the northeastern QTP. Our fieldwork identified populations of P. vlangalii on the northern slope of the Kunlun–Arjin Mountains, similar to the controversial subspecies P. v. lidskii. We analyzed 130 individuals from the northern slope of the Kunlun–Arjin–Qilian Mountains and 253 individuals from GenBank, using three mitochondrial genes and two nuclear genes to assess intraspecific differentiation and demographic history. We found high haplotype diversity and low nucleotide diversity in P. vlangalii, with phylogenetic analyses revealing six distinct clades. Clade VI, confirmed as P. v. lidskii, and Clade IV, a new genetic lineage, were identified alongside three recognized subspecies. Genetic variation was largely attributed to clade splitting, indicating significant divergence. The Mantel test indicated that geographical and environmental factors drove population differentiation. Bayesian molecular clock analysis suggested that the most recent common ancestor of P. vlangalii lived 2.55 million years ago, influenced by the Qinghai–Tibet Movement and glacial cycles. Demographic history and ecological niche modeling (ENM) indicated no population decline during the Last Glacial Maximum, supporting the glacial maximum expansion model, with ENM predicting future habitat expansion for P. vlangalii. In addition, morphological data from 13 meristic and 15 metric characters confirmed clade differences. Our findings significantly advance our understanding of P. vlangalii diversification, population dynamics and response to geological and climatic changes in the QTP.