bluuebunny/crossref_metadata_2025 huggingface dataset:
Ghrelin regulating liver activity and its potential effects on liver fibrosis and Echinococcosis
Authors: Zhu Jiang , Zhou Tanfang , Menggen Meng , Aimulajiang Kalibixiati , Wen Hao
Published: January 2024

Ghrelin widely exists in the central nervous system and peripheral organs, and has biological activities such as maintaining energy homeostasis, regulating lipid metabolism, cell proliferation, immune response, gastrointestinal physiological activities, cognition, memory, circadian rhythm and reward effects. In many benign liver diseases, it may play a hepatoprotective role against steatosis, chronic inflammation, oxidative stress, mitochondrial dysfunction, endoplasmic reticulum stress and apoptosis, and improve liver cell autophagy and immune response to improve disease progression. However, the role of Ghrelin in liver Echinococcosis is currently unclear. This review systematically summarizes the molecular mechanisms by which Ghrelin regulates liver growth metabolism, immune-inflammation, fibrogenesis, proliferation and apoptosis, as well as its protective effects in liver fibrosis diseases, and further proposes the role of Ghrelin in liver Echinococcosis infection. During the infectious process, it may promote the parasitism and survival of parasites on the host by improving the immune-inflammatory microenvironment and fibrosis state, thereby accelerating disease progression. However, there is currently a lack of targeted in vitro and in vivo experimental evidence for this viewpoint.
Transnational governance standards in ensuring sustainable development and operation of hydropower projects in transboundary basins
Authors: McIntyre Owen
Published: January 2024

The notion of “transnational” law encompasses a sophisticated corpus of globally applicable rules, standards and safeguards, often informal in origin, which are widely accepted around the world and supported across a range of business sectors and civil society constituencies. The recent proliferation of such “transnational” law extends to the hydropower sector, where normative standards and safeguards increasingly apply to promote and certify sustainable practices in the development and operation of hydropower projects. Such projects are associated with significant environmental and social impacts and the projected increase in hydropower investments, mainly in emerging economies, will require effective supplemental regulatory tools. Many such projects will be located in, or impact upon, international rivers, thereby adding a further layer of complexity regarding their effective regulation and increased the risk of inter-State disputes over the equitable use of shared waters. Such complexity and risk will be exacerbated by increased uncertainty due to climate change. Thus, the existence of widely accepted transnational standards, which are relevant and applicable to hydropower development globally, can play a key role in building trust between watercourse States and in promoting greater transboundary water cooperation. This article explores the potential role of transnational standards in improved regulation of environmental and social impacts associated with hydropower projects located on international watercourses and the extent to which such standards cohere with established and emerging requirements of international water law. It thus examines the synergies arising between these informal and formal regulatory frameworks with a view to developing a better understanding of their interaction in practice. In so doing, it focuses on two key categories of applicable transnational regime: a sustainability certification and labeling scheme dedicated to hydropower projects and operated by the Hydropower Sustainability Council; and MDB environmental and social safeguard standards imposed upon major water-related projects, including hydropower projects, particularly those adopted by the World Bank and the European Bank for Reconstruction and Development (EBRD).
Designing understandable, action-oriented, and well-perceived earthquake risk maps—The Swiss case study
Authors: Dallo Irina , Schnegg Laura N. , Marti Michèle , Fulda Donat , Papadopoulos Athanasios N. , Roth Philippe , Danciu Laurentiu , Valenzuela Nadja , Wenk Simon R. , Bergamo Paolo , Haslinger Florian , Fäh Donat , Kästli Philipp , Wiemer Stefan
Published: January 2024

With seismic risk assessments becoming more available and reliable over the last years, the need to communicate seismic risk emerged. Seismic risk allows people to understand what impacts earthquakes can have and how they could affect their lives. In Switzerland, a nation-wide seismic risk model (ERM-CH23) was published in 2023 demanding sophisticated communication products to inform about its results. Since only limited research has been conducted on how to best communicate earthquake risk information to societies including the general public, key elements of the outreach activities were tested before the model release. To this end, we, an interdisciplinary group, conducted a nationwide survey in Switzerland in December 2022 to test different earthquake risk map designs by varying the color scale and the legend type. We analyzed the effects of the map and legend design on people's correct interpretation of the risk information, perceived usefulness, risk perception, and motivation to take action. Our survey revealed that (i) a legend with the combination of qualitative and quantitative labels leads to more accurate interpretations of the information presented on the map and is preferred by the public; (ii) the color scale determines how people perceive the spatial risk; and (iii) personal factors influence people's interpretation skills, risk perception, and intention to take action. Our study thus provides insights and recommendations on how to best design user-centered earthquake risk maps as a key outreach product to ensure their effective use by the public, consequently enhancing society's resilience to earthquakes in the long term.
Prediction models for major adverse cardiovascular events after percutaneous coronary intervention: a systematic review
Authors: Deng Wenqi , Wang Dayang , Wan Yandi , Lai Sijia , Ding Yukun , Wang Xian
Published: January 2024

Background

The number of models developed for predicting major adverse cardiovascular events (MACE) in patients undergoing percutaneous coronary intervention (PCI) is increasing, but the performance of these models is unknown. The purpose of this systematic review is to evaluate, describe, and compare existing models and analyze the factors that can predict outcomes.

Methods

We adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 during the execution of this review. Databases including Embase, PubMed, The Cochrane Library, Web of Science, CNKI, Wanfang Data, VIP, and SINOMED were comprehensively searched for identifying studies published from 1977 to 19 May 2023. Model development studies specifically designed for assessing the occurrence of MACE after PCI with or without external validation were included. Bias and transparency were evaluated by the Prediction Model Risk Of Bias Assessment Tool (PROBAST) and Transparent Reporting of a multivariate Individual Prognosis Or Diagnosis (TRIPOD) statement. The key findings were narratively summarized and presented in tables.

Results

A total of 5,234 articles were retrieved, and after thorough screening, 23 studies that met the predefined inclusion criteria were ultimately included. The models were mainly constructed using data from individuals diagnosed with ST-segment elevation myocardial infarction (STEMI). The discrimination of the models, as measured by the area under the curve (AUC) or C-index, varied between 0.638 and 0.96. The commonly used predictor variables include LVEF, age, Killip classification, diabetes, and various others. All models were determined to have a high risk of bias, and their adherence to the TRIPOD items was reported to be over 60%.

Conclusion

The existing models show some predictive ability, but all have a high risk of bias due to methodological shortcomings. This suggests that investigators should follow guidelines to develop high-quality models for better clinical service and dissemination.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=400835, Identifier CRD42023400835.
In-hospital outcomes predictors and trends of redo sternotomy aortic root replacements: insights from a UK registry analysis
Authors: Fudulu Daniel P. , Dong Tim , Kota Rahul , Sinha Shubhra , Chan Jeremy , Rajakaruna Cha , Dimagli Arnaldo , Angelini Gianni D. , Ahmed Eltayeb Mohamed
Published: January 2024

Background

Redo sternotomy aortic root surgery is technically demanding, and the evidence on outcomes is mostly from retrospective, small sample, single-centre studies. We report the trend, early clinical results and outcome predictors of redo aortic root replacement over 20 years in the United Kingdom.

Methods

We retrospectively analysed collected data from the UK National Adult Cardiac Surgery Audit (NACSA) on all redo sternotomy aortic root replacements performed between 30th January 1998 and 19th March 2019. We analysed trends in the volume of operations, characteristics of hospital survivors vs. non-survivors, and predictors of in-hospital outcomes.

Results

During the study period, 1,107 redo sternotomy aortic root replacements were performed (median age 59, 26% of patients were females). Eighty-four per cent of cases (N = 931) underwent a composite root replacement, 11% (N = 119) had homograft root replacement and valve-sparing root replacement was performed in 5.1% (N = 57) of cases. There was a steady increase in the volume of redo sternotomy root replacements beyond 2006, from an annual volume of 22 procedures in 2006 to 106 procedures in 2017. Hospital mortality was 17% (n = 192), postoperative stroke or TIA occurred in 5.2% (n = 58), and postoperative dialysis was required in 11% (n = 109) of patients. Return to the theatre for bleeding/tamponade was required in 9% (n = 102) and median in-hospital stay was 9 days. Age >59 (OR: 2.99, CI: 1.92–4.65, P < 0.001), recent myocardial infarction (OR: 6.42, CI: 2.24–18.41, P = 0.001) were associated with increased in-hospital mortality. Emergency surgery (OR: 3.95, 2.27–6.86, P < 0.001), surgery for endocarditis (OR: 2.05, CI: 1.26–3.33, P = 0.001), salvage coronary artery bypass grafting (OR: 2.20, CI: 1.37–3.54, P < 0.001), arch surgery (OR: 2.47, CI: 1.30–3.61, P = 0.018) and aortic cross-clamp longer than 169 min (OR: 2.17, CI: 1.00–1.01, P = 0.003) were associated with increased risk of mortality. We found no effect of the centre or surgeon volume on mortality (P > 0.05).

Conclusions

Redo sternotomy aortic root replacement still carries significant morbidity and mortality and is sporadically performed across surgeons and centres in the UK.
Metabolic remodeling in cardiac hypertrophy and heart failure with reduced ejection fraction occurs independent of transcription factor EB in mice
Authors: Dörmann Niklas , Hammer Elke , Struckmann Karlotta , Rüdebusch Julia , Bartels Kirsten , Wenzel Kristin , Schulz Julia , Gross Stefan , Schwanz Stefan , Martin Elisa , Fielitz Britta , Pablo Tortola Cristina , Hahn Alexander , Benkner Alexander , Völker Uwe , Felix Stephan B. , Fielitz Jens
Published: January 2024

Background

A metabolic shift from fatty acid (FAO) to glucose oxidation (GO) occurs during cardiac hypertrophy (LVH) and heart failure with reduced ejection fraction (HFrEF), which is mediated by PGC-1α and PPARα. While the transcription factor EB (TFEB) regulates the expression of both PPARGC1A/PGC-1α and PPARA/PPARα, its contribution to metabolic remodeling is uncertain.

Methods

Luciferase assays were performed to verify that TFEB regulates PPARGC1A expression. Cardiomyocyte-specific Tfeb knockout (cKO) and wildtype (WT) male mice were subjected to 27G transverse aortic constriction or sham surgery for 21 and 56 days, respectively, to induce LVH and HFrEF. Echocardiographic, morphological, and histological analyses were performed. Changes in markers of cardiac stress and remodeling, metabolic shift and oxidative phosphorylation were investigated by Western blot analyses, mass spectrometry, qRT-PCR, and citrate synthase and complex II activity measurements.

Results

Luciferase assays revealed that TFEB increases PPARGC1A/PGC-1α expression, which was inhibited by class IIa histone deacetylases and derepressed by protein kinase D. At baseline, cKO mice exhibited a reduced cardiac function, elevated stress markers and a decrease in FAO and GO gene expression compared to WT mice. LVH resulted in increased cardiac remodeling and a decreased expression of FAO and GO genes, but a comparable decline in cardiac function in cKO compared to WT mice. In HFrEF, cKO mice showed an improved cardiac function, lower heart weights, smaller myocytes and a reduction in cardiac remodeling compared to WT mice. Proteomic analysis revealed a comparable decrease in FAO- and increase in GO-related proteins in both genotypes. A significant reduction in mitochondrial quality control genes and a decreased citrate synthase and complex II activities was observed in hearts of WT but not cKO HFrEF mice.

Conclusions

TFEB affects the baseline expression of metabolic and mitochondrial quality control genes in the heart, but has only minor effects on the metabolic shift in LVH and HFrEF in mice. Deletion of TFEB plays a protective role in HFrEF but does not affect the course of LVH. Further studies are needed to elucidate if TFEB affects the metabolic flux in stressed cardiomyocytes.
Case Report: The application of amplatzer vascular plug to repair aortic dissection intimal tears and false lumen
Authors: Li Ruihua , Liu Yang , Jiang Jianjun
Published: January 2024

In recent years, significant advancements have been made in endovascular therapy for aortic dissection, resulting in the development of various treatment methods. Nevertheless, there is a contentious discussion regarding the suitability of different treatment methods for addressing the unique features of individual lesions. Specifically, the matter of whether the presence of small intimal tears or multiple distal tears requires extensive aortic coverage with graft stents, which may block the blood supply to important organs, intercostal arteries, or lumbar arteries, remains unresolved. Further research is necessary to determine the need for complex fenestrated or branched endovascular aortic repair (F/B-EVAR) in the management of chronic post-dissection aneurysms involving visceral arteries. Our report highlights the successful endovascular repair of three patients with aortic dissection, encompassing one Stanford A type and two Stanford B types. Utilizing the Amplatzer Vascular Plug (AVP) alone or in combination with the coil embolization technique, we achieved favorable clinical outcomes. This article aims to provide valuable insights and new perspectives on the tailored management of aortic dissection by conducting a comprehensive examination of the subtle differences in the treatment processes and techniques applied to these three patients.
CTAB-GAN+: enhancing tabular data synthesis
Authors: Zhao Zilong , Kunar Aditya , Birke Robert , Van der Scheer Hiek , Chen Lydia Y.
Published: January 2024

The usage of synthetic data is gaining momentum in part due to the unavailability of original data due to privacy and legal considerations and in part due to its utility as an augmentation to the authentic data. Generative adversarial networks (GANs), a paragon of generative models, initially for images and subsequently for tabular data, has contributed many of the state-of-the-art synthesizers. As GANs improve, the synthesized data increasingly resemble the real data risking to leak privacy. Differential privacy (DP) provides theoretical guarantees on privacy loss but degrades data utility. Striking the best trade-off remains yet a challenging research question. In this study, we propose CTAB-GAN+ a novel conditional tabular GAN. CTAB-GAN+ improves upon state-of-the-art by (i) adding downstream losses to conditional GAN for higher utility synthetic data in both classification and regression domains; (ii) using Wasserstein loss with gradient penalty for better training convergence; (iii) introducing novel encoders targeting mixed continuous-categorical variables and variables with unbalanced or skewed data; and (iv) training with DP stochastic gradient descent to impose strict privacy guarantees. We extensively evaluate CTAB-GAN+ on statistical similarity and machine learning utility against state-of-the-art tabular GANs. The results show that CTAB-GAN+ synthesizes privacy-preserving data with at least 21.9% higher machine learning utility (i.e., F1-Score) across multiple datasets and learning tasks under given privacy budget.
A novel approach to fake news classification using LSTM-based deep learning models
Authors: Padalko Halyna , Chomko Vasyl , Chumachenko Dmytro
Published: January 2024

The rapid dissemination of information has been accompanied by the proliferation of fake news, posing significant challenges in discerning authentic news from fabricated narratives. This study addresses the urgent need for effective fake news detection mechanisms. The spread of fake news on digital platforms has necessitated the development of sophisticated tools for accurate detection and classification. Deep learning models, particularly Bi-LSTM and attention-based Bi-LSTM architectures, have shown promise in tackling this issue. This research utilized Bi-LSTM and attention-based Bi-LSTM models, integrating an attention mechanism to assess the significance of different parts of the input data. The models were trained on an 80% subset of the data and tested on the remaining 20%, employing comprehensive evaluation metrics including Recall, Precision, F1-Score, Accuracy, and Loss. Comparative analysis with existing models revealed the superior efficacy of the proposed architectures. The attention-based Bi-LSTM model demonstrated remarkable proficiency, outperforming other models in terms of accuracy (97.66%) and other key metrics. The study highlighted the potential of integrating advanced deep learning techniques in fake news detection. The proposed models set new standards in the field, offering effective tools for combating misinformation. Limitations such as data dependency, potential for overfitting, and language and context specificity were acknowledged. The research underscores the importance of leveraging cutting-edge deep learning methodologies, particularly attention mechanisms, in fake news identification. The innovative models presented pave the way for more robust solutions to counter misinformation, thereby preserving the veracity of digital information. Future research should focus on enhancing data diversity, model efficiency, and applicability across various languages and contexts.
The impact of Oligo-Miocene basaltic intrusions on the petroleum system in Gulf of Suez rift basin, Egypt: new insights into thermal maturity and reservoir quality
Authors: Elmaadawy Khaled G. , Bayan Mahmoud F. , Gad Mohamed , Szűcs Péter , Eid Mohamed Hamdy , Abukhadra Mostafa R. , El-Sherbeeny Ahmed M. , Bellucci Stefano , Abdelmaksoud Ashraf S.
Published: January 2024

In recent years, the petroleum industry has prioritized the exploration of new and unconventional petroleum reservoirs. As a result, this study assessed the significance of basaltic intrusions from two key aspects: their impact on the thermal maturity of pre-rift source rocks and their potentiality as reservoirs. The present study attempts to integrate surface field investigations of basaltic dykes in Wadi Nukhul and Wadi Matulla as surface analogs with petroleum system modeling of pre-rift source rocks containing subsurface basaltic intrusions in the Abu Rudeis-Sidri field. Therefore, the fracture networks were observed in Wadi Nukhul and Wadi Matulla, suggesting that both the basaltic dykes and host rocks have interconnected fractures, which is critical for a high-quality reservoir of the dykes and efficient oil expulsion. As a result, the analysis of burial history, temperature, maturity, generation, transformation ratio, and expelled oil quantity revealed a significantly high value for basaltic intrusions. Moreover, the Abu Rudeis-Sidri field had a good petroleum system with thermally mature source rocks by basaltic intrusions. Furthermore, the fractured basaltic intrusions presented a high-quality oil reservoir well-sealed by the thick Rudeis Formation. Oil production has doubled since the discovery of this reservoir. This study introduces a novel approach to understanding the distribution pattern of basaltic intrusions in subsurface and surface analogs, which can serve as a model for exploring new potential unconventional basaltic reservoirs in the Gulf of Suez rift basin.
Enhancing rock and soil hazard monitoring in open-pit mining operations through ultra-short-term wind speed prediction
Authors: Sun Pengxiang , Wang Juan , Yan Zhenguo
Published: January 2024

Wind speed exacerbates challenges associated with rock stability, introducing factors such as heightened erosion and the possibility of particle loosening. This increased sensitivity to erosion can result in material displacement, thereby compromising the overall stability of rock layers within the open-pit mining site. Therefore, accurate wind speed predictions are crucial for understanding the impact on rock stability, ensuring the safety and efficiency of open-pit mining operations. While most existing studies on wind speed prediction primarily focus on making overall predictions from the entire wind speed sequence, with limited consideration for the stationarity characteristics of the sequence, This paper introduces a novel approach for effective monitoring and early warning of geotechnical hazards. Our proposed method involves dividing wind speed data into stationary and non-stationary segments using the sliding window average method within the threshold method, validated by the Augmented Dickey-Fuller test. Subsequently, we use temporal convolutional networks (TCN) with dilated causal convolution and long short-term memory to predict the stationary segment of wind speed, effectively improving prediction accuracy for this segment. For the non-stationary segment, we implement complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to reduce sequence complexity, followed by TCN with an attention mechanism (ATTENTION) to forecast wind speed one step ahead. Finally, we overlay the predictions of these two segments to obtain the final prediction. Our proposed model, tested with data from an open-pit mining area in western China, achieved promising results with an average absolute error of 0.14 knots, mean squared error of 0.05 knots2, and root mean squared error of 0.20 knots. These findings signify a significant advancement in the accuracy of short-term wind speed prediction. This advancement not only enables the rapid assessment and proactive response to imminent risks but also contributes to geotechnical hazard monitoring in open-pit mining operations.
Snowfall deposition in mountainous terrain: a statistical downscaling scheme from high-resolution model data on simulated topographies
Authors: Helbig Nora , Mott Rebecca , Bühler Yves , Le Toumelin Louis , Lehning Michael
Published: January 2024

One of the primary causes of non-uniform snowfall deposition on the ground in mountainous regions is the preferential deposition of snow, which results from the interaction of near-surface winds with topography and snow particles. However, producing high-resolution snowfall deposition patterns can be computationally expensive due to the need to run full atmospheric models. To address this, we developed two statistical downscaling schemes that can efficiently downscale near-surface, low-resolution snowfall data to fine-scale snow deposition accounting for the effect of preferential deposition in mountainous regions. Our approach relies on a comprehensive, model database generated using 3D wind fields from an atmospheric model and a preferential deposition model on several thousand simulated topographies covering a broad range in terrain characteristics. Both snowfall downscaling schemes rely on fine-scale topographic scaling parameters and low-resolution wind speed as input. While one scheme, referred to as the “wind scheme”, further necessitates fine-scale vertical wind components, a second scheme, referred to as the “aspect scheme”, does not require fine-scale temporal input. We achieve this by additionally downscaling near-surface vertical wind speed solely using topographic scaling parameters and low-resolution wind direction. We assess the performance of our downscaling schemes using an independent subset of the model database on simulated topographies, model data on actual terrain, and spatially measured new snow depth obtained through a photogrammetric drone survey following a snowfall event on previously snow-free ground. While the assessments show that our downscaling schemes perform well (relative errors ≤ ±3% with modeled and ≤ ±6% with measured snowfall deposition), they also demonstrate comparable results to benchmark downscaling models. However, our schemes notably outperform the benchmark models in representing fine-scale patterns. Our downscaling schemes possess several key features, including high computational efficiency, versatility enabled by the comprehensive model database, and independence from fine-scale temporal input data (aspect scheme), indicating their potential for widespread applicability. Therefore, our downscaling schemes for near-surface snowfall and vertical wind speed can be beneficial for various applications at fine grid resolutions such as in atmospheric and climate sciences, snow hydrology, glaciology, remote sensing, and avalanche sciences.
Multi-data settlement prediction along a road section integrating InSAR and coastal subsurface information with data assimilation
Authors: Verberne Manon , Koster Kay , Fokker Peter A.
Published: January 2024

This paper presents a novel approach to examining the impact of soil settlement and its spatial distribution on infrastructure. The study focuses on a specific road section in the Friesland coastal plain in the north of the Netherlands, investigating how the Holocene coastal subsurface architecture influences settlement patterns. Our study underscores the importance of integrating multiple datasets, providing data at varying resolutions. The road segment traverses lithostratigraphical units, which include tidal channel and tidal flat deposits, overlaying an older tidal basin system and intercalated peat beds. Through data assimilation of a settlement model optimized with InSAR measurements, we have identified settlement heterogeneities that can be explained by combining high-resolution variations in lithology with gradual changes in lithostratigraphy. This was accomplished by utilizing a medium-resolution model (MRM) based on borehole descriptions and a high-resolution data (HRD) approach based on cone penetration tests along the road. The HRD method proved more effective in capturing abrupt changes in lithology between channel structures, while the MRM provided a continuous representation of the lithostratigraphic setting of the area. Our study demonstrates that subsurface heterogeneities have significant implications for subsidence along roads. Settlement rates increase from 2–4 mm/year towards 9 mm/year along the road section, resulting in a differential settlement of more than 5 mm/year over a distance of less than a kilometer. This is primarily attributed to variations in lithostratigraphy. Overall, this new innovative approach offers a practical and cost-effective solution for predicting subsidence due to settlement, eliminating the need for expensive laboratory tests. By integrating lithology and lithostratigraphy, more efficient road maintenance and management become possible.
Flood mapping of the lower Mejerda Valley (Tunisia) using Sentinel-1 SAR: geological and geomorphological controls on flood hazard
Authors: Khemiri Lamia , Katlane Rim , Khelil Mannoubi , Gaidi Seifeddine , Ghanmi Mohamed , Zargouni Fouad
Published: January 2024

Understanding the influence of the hydrological regime changes, encompassing both the duration and spatial extent of floods, is explored, through this paper, in the context of the complex interactions of the geological, geomorphological and climate change conditions. Integrating these parameters and their combined influence becomes paramount for effective flood risk management and disaster prevention, as highlighted in the broader context of the study’s conclusions. Over the past decade, despite prevailing drought conditions in North African countries, the Mejerda Valley in Tunisia has experienced several major flood events. The valley geomorphological history is presented, within the landscape evolution. This study explores the use of Sentinel-1 radar data for detecting and managing floods in the region, with a particular emphasis on the vulnerability of the Lower Mejerda Valley. Sentinel-1 radar data, owing to their continuous monitoring capabilities independent of weather conditions, prove highly effective in tracking the temporal evolution of floods and accurately mapping the extent of affected areas. The methodology utilized in this study has proven to be highly effective in accurately identifying areas susceptible to flooding, both spatially and temporally. In generating classified flood images, water objects are highlighted by applying a specific formula. The study delves into significant flood events in the Mejerda Valley, including occurrences in 2015, 2017, 2019, and 2020, examining their profound impacts on various regions. For instance, the floods of 2015 recorded precipitation levels reaching up to 141 mm, contributing to the overall understanding of flood evolution in the region. In conclusion, the Mejerda Delta’s relief is primarily due to tectonism, influencing both Mio-Pliocene and Quaternary processes, shaping the current delta configuration. The Valley’s topography results from extensive geomorphological evolution, with the eastward shoreline advance leading to the formation of sebkhas and lagoons, indicators of high flood risk, supported by detailed flood event analysis. Moreover, The climate change and anthropic activity are non-negligible parameters influencing flood occurrence and intensity.
Dropout in Andalusian universities: prediction and prevention
Authors: Fernández Cruz Manuel , Álvarez Ferrándiz Daniel , Fernández García-Valdecasas F. Borja , González Castellón Esther
Published: January 2024

Problem and objective

University dropout is a major problem that affects more than 31,000 students each year in Andalusian universities, with serious personal and social consequences and an economic cost of more than 222 million euros for the region’s public administration. As concluded from the review of explanatory models we reviewed, dropout has a multicausal origin. The purpose of our work is to test the efficacy of the use of a screening for the early detection of the risk of academic dropout in Higher Education in Andalusian universities.

Procedure

We applied a screening instrument adapted for incoming students in public universities in Andalusia. The survey was applied at the beginning of the second semester. In this article we present data from a sample composed of 976 subjects from the universities of Granada UGR, Jaén UJA and Pablo de Olavide de Sevilla UPO.

Results

With the data obtained we have established the dropout risk group, which includes those students who do not reach an average score of 3.00 in the total screening. There are 34 students representing 3.48% of the sample. Of these 34 students, 26 are women and 8 are men; 20 belong to the UGR, 8 to the UJA and 5 to the UPO. The detection of the risk group will allow the universities to apply preventive measures in a personalized and adjusted way to avoid possible dropout.
The explanatory power of Carnegie Classification in predicting engagement indicators: a multilevel analysis
Authors: Gök Enes , Aydin Burak
Published: January 2024

The study aims to explore the effect of the type of higher education institution on students’ engagement. The meta-analyses of multilevel regression coefficients revealed significant relationships between the type of higher education institution and student engagement indicators across the years from 2013 to 2019. Comparing different types of higher education institutions with the base category, our findings revealed significant differences in effective teaching practices, discussion with diverse others, and student-faculty interaction consistent throughout the years. These findings are expected to provide insights for institutional administrators, policymakers, and researchers given that student engagement in higher education has become an indicator of quality all around the world.
The ethical implications of using generative chatbots in higher education
Authors: Williams Ryan Thomas
Published: January 2024

Incorporating artificial intelligence (AI) into education, specifically through generative chatbots, can transform teaching and learning for education professionals in both administrative and pedagogical ways. However, the ethical implications of using generative chatbots in education must be carefully considered. Ethical concerns about advanced chatbots have yet to be explored in the education sector. This short article introduces the ethical concerns associated with introducing platforms such as ChatGPT in education. The article outlines how handling sensitive student data by chatbots presents significant privacy challenges, thus requiring adherence to data protection regulations, which may not always be possible. It highlights the risk of algorithmic bias in chatbots, which could perpetuate societal biases, which can be problematic. The article also examines the balance between fostering student autonomy in learning and the potential impact on academic self-efficacy, noting the risk of over-reliance on AI for educational purposes. Plagiarism continues to emerge as a critical ethical concern, with AI-generated content threatening academic integrity. The article advocates for comprehensive measures to address these ethical issues, including clear policies, advanced plagiarism detection techniques, and innovative assessment methods. By addressing these ethical challenges, the article argues that educators, AI developers, policymakers, and students can fully harness the potential of chatbots in education, creating a more inclusive, empowering, and ethically sound educational future.
Crosstalk between proximal tubular epithelial cells and other interstitial cells in tubulointerstitial fibrosis after renal injury
Authors: Guo Congcong , Cui Yuying , Jiao Mingwen , Yao Jinming , Zhao Junyu , Tian Yutian , Dong Jianjun , Liao Lin
Published: January 2024

The energy needs of tubular epithelial components, especially proximal tubular epithelial cells (PTECs), are high and they heavily depend on aerobic metabolism. As a result, they are particularly vulnerable to various injuries caused by factors such as ischemia, proteinuria, toxins, and elevated glucose levels. Initial metabolic and phenotypic changes in PTECs after injury are likely an attempt at survival and repair. Nevertheless, in cases of recurrent or prolonged injury, PTECs have the potential to undergo a transition to a secretory state, leading to the generation and discharge of diverse bioactive substances, including transforming growth factor-β, Wnt ligands, hepatocyte growth factor, interleukin (IL)-1β, lactic acid, exosomes, and extracellular vesicles. By promoting fibroblast activation, macrophage recruitment, and endothelial cell loss, these bioactive compounds stimulate communication between epithelial cells and other interstitial cells, ultimately worsening renal damage. This review provides a summary of the latest findings on bioactive compounds that facilitate the communication between these cellular categories, ultimately leading to the advancement of tubulointerstitial fibrosis (TIF).
Risk factors of cerebrospinal fluid leakage after neuroendoscopic transsphenoidal pituitary adenoma resection: a systematic review and meta-analysis
Authors: Zhao Jiahui , Wang Shisong , Zhao Xudong , Cui Haohao , Zou Cunyi
Published: January 2024

Introduction

Cerebro spinal fluid (CSF) leakage is common and might lead to severe postoperative complications after endoscopic transsphenoidal pituitary adenoma resection. However, the risk factors of postoperative CSF leakage are still controversial. This article presents a systematic review to explore the explicit risk factors of CSF leakage after endoscopic transsphenoidal pituitary adenomere section.

Methods

PRISMA and AMSTAR guidelines were followed to assess the methodological quality of the systematic review. PubMed, Medline, Embase, Web of Science, Cochrane, Clinical Trails, CNKI, CBM, Wan Fang, and VIP databases were searched for all studies on postoperative CSF leak risk factors. The quality of the included studies was assessed by the Newcastle-Ottawa scale. Review Manager 5.4 software was used to calculate the pooled effect size of potential factors with statistical significance.

Results

A total of 6775 patients with pituitary adenoma across 18 articles were included, containing 482 cases of postoperative CSF leakage (accounting for 7.11%). All of the articles had a quality score > 5, indicating good quality. Meta-analysis showed that an increased risk of CSF leak was found for higher levels of BMI (MD=1.91, 95% CI (0.86,2.96), bigger tumor size [OR=4.93, 95% CI (1.41,17.26)], greater tumor invasion (OR=3.01, 95% CI (1.71, 5.31), the harder texture of tumor [OR=2.65, 95% CI (1.95,3.62)], intraoperative cerebrospinal fluid leakage [OR=5.61, 95% CI (3.53,8.90)], multiple operations [OR=2.27, 95% CI (1.60,3.23)].

Conclusion

BMI, multiple operations, tumor size, tumor invasion, hard texture, and intraoperative cerebrospinal fluid leakage are the risk factors of postoperative CSF leakage. Clinical doctors should pay attention to these risk factors, and conduct strict skull base reconstruction and careful postoperative management.
Assessment of potential risk factors associated with gestational diabetes mellitus: evidence from a Mendelian randomization study
Authors: Fu Qingming , Chen Rumeng , Xu Shuling , Ding Yining , Huang Chunxia , He Binsheng , Jiang Ting , Zeng Bin , Bao Meihua , Li Sen
Published: January 2024

Background

Previous research on the association between risk factors and gestational diabetes mellitus (GDM) primarily comprises observational studies with inconclusive results. The objective of this study is to investigate the causal relationship between 108 traits and GDM by employing a two-sample Mendelian randomization (MR) analysis to identify potential risk factors of GDM.

Methods

We conducted MR analyses to explore the relationships between traits and GDM. The genome-wide association studies (GWAS) for traits were primarily based on data from the UK Biobank (UKBB), while the GWAS for GDM utilized data from FinnGen. We employed a false discovery rate (FDR) of 5% to account for multiple comparisons.

Results

The inverse-variance weighted (IVW) method indicated that the genetically predicted 24 risk factors were significantly associated with GDM, such as “Forced expiratory volume in 1-second (FEV1)” (OR=0.76; 95% CI: 0.63, 0.92), “Forced vital capacity (FVC)” (OR=0.74; 95% CI: 0.64, 0.87), “Usual walking pace” (OR=0.19; 95% CI: 0.09, 0.39), “Sex hormone-binding globulin (SHBG)” (OR=0.86; 95% CI: 0.78, 0.94). The sensitivity analyses with MR-Egger and weighted median methods indicated consistent results for most of the trats.

Conclusion

Our study has uncovered a significant causal relationship between 24 risk factors and GDM. These results offer a new theoretical foundation for preventing or mitigating the risks associated with GDM.
A combined analysis of TyG index, SII index, and SIRI index: positive association with CHD risk and coronary atherosclerosis severity in patients with NAFLD
Authors: Dong Wenyuan , Gong Yuxin , Zhao Jianqi , Wang Yanan , Li Bao , Yang Youdong
Published: January 2024

Background

Insulin resistance(IR) and inflammation have been regarded as common potential mechanisms in coronary heart disease (CHD) and non-alcoholic fatty liver disease (NAFLD). Triglyceride-glucose (TyG) index is a novel biomarker of insulin resistance, System immune-inflammation index(SII) and Systemic inflammation response index(SIRI) are novel biomarkers of inflammation, these biomarkers have not been studied in CHD with NAFLD patients. This study investigated the correlation between the TyG index, SII index, and SIRI index and CHD risk among NAFLD patients.

Methods

This cross-sectional study included 407 patients with NAFLD in the Department of Cardiology, The Second Hospital of Shanxi Medical University. Of these, 250 patients with CHD were enrolled in the NAFLD+CHD group and 157 patients without CHD were enrolled as NAFLD control. To balance covariates between groups, 144 patients were selected from each group in a 1:1 ratio based on propensity score matching (PSM). Potential influences were screened using Lasso regression analysis. Univariate and multivariate logistic regression analyses and the Least Absolute Shrinkage and Selection Operator (LASSO) regression were used to assess independent risk and protective factors for CHD. Construction of nomogram using independent risk factors screened by machine learning. The receiver operating characteristic(ROC) curve was used to assess the ability of these independent risk factors to predict coronary heart disease. The relationship between the Gensini score and independent risk factors was reflected using the Sankey diagram.

Results

The LASSO logistic regression analysis and Logistic regression analyses suggest that TyG index (OR, 2.193; 95% CI, 1.242-3.873; P = 0.007), SII index (OR, 1.002; 95% CI, 1.001-29 1.003; P <0.001), and SIRI index (OR,1.483;95%CI,1.058-2.079,P=0.022) are independent risk factors for CHD. At the same time, Neutrophils, TG, and LDL-C were also found to be independent risk factors in patients, HDL-C was a protective factor for CHD in patients with NAFLD. Further analysis using three machine learning algorithms found these independent risk factors to have good predictive value for disease diagnosis, SII index shows the highest predictive value. ROC curve analysis demonstrated that combining the SII index, SIRI index, and TyG index can improve the diagnostic ability of non-alcoholic liver cirrhosis patients with CHD.ROC curve analysis showed that the combined analysis of these independent risk factors improved the predictive value of CHD(AUC: 0.751; 95% CI: 0.704-0.798; P <0.001).

Conclusion

TyG index, SII index, and SIRI index are all independent risk factors for CHD in patients with NAFLD and are strongly associated with prediction and the severity of CHD.
Thyroid function and thyroid homeostasis parameters are associated with increased urinary albumin excretion in euthyroid individuals over 60 years old from NHANES
Authors: Liu Xue , Li Yuchen , Chai Yuwei , Zhang Yuhao , Zhang Li , Zhang Haiqing
Published: January 2024

Introduction

The relationship between thyroid function/homeostasis parameters and renal function has been extensively studied. However, the relationship between thyroid function and thyroid homeostasis parameters with albuminuria among elderly individuals remains unclear.

Methods

The population was divided into an albuminuria group and a non-albuminuria group for baseline characteristic difference analysis. Multivariable logistic regression was used to test the association between thyroid function, and thyroid homeostasis parameters and albuminuria. The nonlinear relationship was explored with restricted cubic splines. Meanwhile, we investigated whether the relationship also existed in the diabetes and hypertension subgroups. Receiver operating characteristic (ROC) curves were used to assess the effectiveness of the indices.

Results

FT4 and TFQIFT4 were positively correlated with albuminuria (OR = 1.12; 95% CI = 1.02–1.23, p = 0.02; OR = 1.79; 95% CI = 1.08–2.99, p = 0.03), and FT3/FT4 was negatively correlated with albuminuria (OR = 0.03; 95% CI = 0.00–0.26, p = 0.003). Additionally, the nonlinear relationship between FT3/FT4 as well as TSHI and albuminuria was approximately U-shaped. Similar results were observed in the hypertension subgroup but not in the diabetes subgroup. There was a U-shaped nonlinear relationship between FT3 and albuminuria in the diabetes group. In addition, FT3/FT4 performed better than TFQI, TT4RI, and TSHI in ROC analyses for albuminuria prediction.

Conclusion

FT4, TFQIFT4, and a low FT3/FT4 ratio were risk factors for albuminuria in euthyroid individuals over 60 years old. However, FT3 was more associated with albuminuria in the diabetes subgroup. TSH was not associated with albuminuria in any analysis. In our study, we attempted to provide more reasonable thyroid parameters and basis for evaluating patients with underlying albuminuria. FT3/FT4 may be used as a helpful indicator to predict albuminuria and provide novel ideas for the evaluation and treatment of albuminuria.
Predicted visceral adiposity index in relation to risk of coronary heart disease and all-cause mortality: insights from NHANES
Authors: Luo Yixing , Zhan Xiangpeng , Liu Yang , Chen Luyao , Zhu Liang , Cai Wenyao
Published: January 2024

Background and aims

The Visceral Adiposity Index (VAI) is a straightforward and gender-specific marker that combines anthropometric measurements with lipid profiles. The objective of this study was to evaluate the relationship between VAI and coronary heart disease (CHD).

Methods and results

The study examined data collected from adults during the NHANES 1999-2018 cycle. The analyses were weighted, and multivariable logistic regression models were employed to investigate the association between VAI and CHD. Additionally, subgroup analyses stratified by age were conducted. To evaluate the impact of VAI levels on survival outcomes, the study utilized the Kaplan-Meier method and performed the log-rank test to evaluate the survival outcome of participants with different VAI levels. The study findings revealed a significant association between VAI and CHD, indicating a non-linear relationship where an increase in VAI was associated with an elevated risk of CHD. High levels of VAI were linked to an increased prevalence of CHD (Q4 vs Q1, OR 1.50, 95% CI 1.12-2.01, P=0.01). Additionally, higher levels of VAI were associated with a poorer overall prognosis in terms of survival outcomes. There were no statistically significant differences in survival outcomes among the population with CHD.

Conclusion

The results of this study highlighted a significant association between VAI and CHD, with a non-linear relationship observed. High VAI levels were associated with an increased risk of CHD and poor survival outcomes, emphasizing the importance of understanding and managing this risk factor, particularly in older age groups.