bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gastric Edema as an Early Indicator of Helicobacter Pylori Infection?
Authors: UNAL Sinem Eser POLAT , CELIK Betul 
Published: December 2024

Abstract

Background
The relationship between Helicobacter pylori (H. pylori) and gastritis has been crucial in understanding gastrointestinal disease. H. pylori gastritis is the most common and curable type of gastritis, impacting over half of the global population.
Aims
Gastric edema may be an early sign of H. pylori infection before the onset of active chronic gastritis. This study aims to highlight the importance of considering H. pylori in biopsies showing edematous gastric mucosa, even in the absence of active inflammation.
Methods
This study included patients with "Edematous gastric mucosa, negative for H. pylori infection" from January 2022 to April 2023. Gastric corpus and cardia biopsies were excluded, and only antral biopsy samples were included to increase the specificity. Histological evaluations were performed with Hematoxylin & Eosin and Giemsa stains. H. pylori colonization was assessed and categorized based on density.
Results
A total of 211 gastric biopsy samples were examined, with 114 eligible for the study. H. pylori was detected in 20 out of 114 cases (17.54%), with a higher prevalence in pediatric patients (20%) compared to geriatric patients (13.33%). The primary complaint was abdominal pain (80%).
Conclusion
Gastric edema may be an early sign of H. pylori infection before the onset of active chronic gastritis. This study highlights the importance of considering H. pylori in biopsies showing edematous gastric mucosa, even in the absence of active inflammation.
1H-Magnetic Resonance Spectroscopy (MRS) in analysis of cerebral metabolite: MRS image for elderly patient anesthesia
Authors: Mao Haoli , Zhu Jiao , Zhang Fengwei , He Huan , Zhou Ren , Suo Chao , Zhang Lei , Jiang Hong 
Published: December 2024

Abstract

Background: The phenomenon of population aging is progress rapidly and globally, indicating more research is needed to target elderly cohort. It’s well-known that general anesthesia can have a neurocognitive impact on elderly patients, affecting their prognosis. However, the underlying mechanism of how general anesthesia affects brain function has not yet been elucidated. The impact of general anesthesia on brain metabolism may be the key to studying the effects of anesthetic drugs on the brain. At present, research on brain metabolism mainly relies on cerebrospinal fluid and animal models, and Magnetic Resonance Spectroscopy (MRS) can explore changes in metabolic products in specific regions of the brain, providing a new non-invasive in vivodetection method for studying the effects of general anesthesia on brain metabolism.
Objective: To evaluate the effect of general anesthesia on brain metabolism before and after aging brain anesthesia, using non-invasive brain MRS method. This experiment is a one arm two sessions longitudinal imaging study aimed at investigating the brain metabolic changes in patients before and after anesthesia induced by general anesthetics.
Method: 30 patients with oral and maxillofacial tumors were randomly selected and evaluated with a cognitive function scale before surgery to ensure that they have no neurocognitive dysfunction. Perform preoperative and one day postoperative head MRS scans testing on patients. The detection sequences included MEGA-PRESS optimsed for GABA detection, and short echo-time as well as long echo-time PRESS sequences at left prefrontal area. MRS data were analyzed and compared using LCModel and TARQUIN. Paired t-test was conducted to detecting metabolites’ change before and after the surgery.
Result: 30 patients were observed to have changes in the prefrontal cortex. We found a significant decrease of GABA concentration using MEGA-PRESS sequence, and a significant increase of Glutamate/Glutamineconcentration detected by both short TE and long TE PRESS sequences.
Effects of intraoperative open-lung strategy on cardiopulmonary function in frail elderly patients undergoing laparoscopic surgery: a randomized controlled trial
Authors: Gao Ju , Ding Yinyin , Huang Tianfeng , Zhu Xiangpeng , Ge Yali , Zhang Yang 
Published: December 2024

Abstract

Purpose
This study aimed to investigate the potential effects of intraoperative open-lung strategy (OLS) on pulmonary function and cardiac function in elderly frail patients.
Methods
104 frail elderly patients were randomly assigned into non-OLS group [small tidal volume (VT) + 5 cm H2O positive end-expiratory pressure (PEEP)] and OLS group [small VT + stepwise recruitment maneuvers (RM) + individualized PEEP]. Primary outcomes assessed were intraoperative cardiopulmonary function indices and incidence of postoperative pulmonary complications. Secondary outcomes included postoperative markers of myocardial injury and Postoperative regression.
Results
Eighty-one patients completed the final analysis. The OLS group showed significant improvements in arterial oxygen pressure (PaO2), oxygenation index (OI), and pulmonary dynamic compliance (Cdyn) from the peak of lung recruitment to the end of surgery (T1-T4). The overall incidence of postoperative pulmonary complications (PPCs) also significantly decreased (P<0.05). Compared with the non-OLS group, left ventricular ejection fraction (LVEF), stroke volume (SV), early mitral inflow velocity to early mitral annular velocity ratio (E/E '), left ventricular global longitudinal strain (LVGLS), and plane systolic offset of mitral and tricuspid annular plane were significantly decreased at T1 in the OLS group (P < 0.05), and recovered at T3. No significant change in the expression of myocardial injury markers between the two groups (P > 0.05). The Postoperative regression time of OLS patients was significantly shortened (P < 0.05).
Conclusion
The application of OLS can effectively improve intraoperative respiratory mechanics and oxygenation in frail elderly patients, reduce the occurrence of PPCs, and improve the prognosis of patients, without continuous negative impact on cardiac function.
Trial registration:
Chinese Clinical Trial Registry, www.chictr.org.cn, number: ChiCTR2200058783; Registered on April 17, 2022.
A Generalized Software Reliability Growth Model Incorporating Testing-Coverage Operating in Random Field Environment with cost function
Authors: Yadav Akshay Kumar , Pant Millie , Srivast Shilpa 
Published: December 2024

Abstract

A human cannot imagine surviving in the current technological era without software, as software manufacturers focus heavily on creating software that is free of bugs and maintains reliability and compatibility with human activities that depend on software-enabled equipment. One important thing to look into is how the software will function in a random field condition. In this chapter, we develop a generalized software reliability growth model with generalized fault coverage function, considering the effects of random field environment. Two data sets are used, and the computational outcomes of the suggested models and the existing models are compared using the Least Square Estimation (LSE) approach in MATLAB software to show which model performs better. For comparison, the three goodness-of-fit metrics, the root mean square error, R-square, and sum of square error are also employed.
Family Resilience Enhances Subjective Wellbeing of Women with Infertility by Reducing the Infertility-Related Stress
Authors: Wang Tingting , Song Xiao , Lin Weiyi , Meng Yueru , Li Yuli 
Published: December 2024

Abstract

Background Women in infertile couples tend to experience more infertility-related stress and more physical and psychological problems due to a variety of reasons. In this study, the impact of infertility on women was explored. We examined the relationship between family resilience and subjective wellbeing, and the mediating role of infertility-related stress among Chinese women with infertility.Methods This cross-sectional study surveyed 403 women with infertility from two reproductive medicine centres in Jinan, Shandong Province, using the General Wellbeing Scheduling, Fertility Problem Inventory, and Family Resilience Assessment Scale. A structural equation model was used to test the relationship between family resilience and subjective wellbeing.Results The total score of family resilience was significantly negatively correlated with the total score of infertility-related stress (r = -0.296, P < 0.01), and positively correlated with the total score of subjective well-being (r = 0.366, P < 0.01). The total score of infertility-related stress was significantly negatively correlated with the total score of subjective well-being (r = -0.431, P < 0.01). Family resilience could directly improve the subjective well-being of women with infertility (95%CI: 0.1036, 0.2472; P < 0.001), which could also indirectly improve subjective well-being by reducing infertility-related stress (95%CI: 0.0401, 0.1258; P < 0.001).Conclusion The results demonstrated that family resilience was negatively correlated with infertility-related stress and positively correlated with subjective wellbeing. Moreover, infertility-related stress mediated the relationship between family resilience and subjective wellbeing. Clinical staff should not only implement strategies to reduce infertility-related stress among women with infertility, but also provide family resilience-based interventions to improve subjective wellbeing of women with infertility.
Augmented Reality Intraoperative Tractography for diffuse glioma microsurgical resection
Authors: Konovalov Anton , Bykanov Andrey , Okishev Dmitry , Artemyev Anton , Knyazev Alexander , Ivanov Vladimir , Smirnov Anton , Strelkov Sergey , Pronin Igor , Pavlova Galina , Pithelauri David , Eliava Shalva 
Published: December 2024

Abstract

This study explores the use of augmented reality (AR) for intraoperative guidance during the microsurgical resection of diffuse gliomas, especially those located near the critical corticospinal tract. AR provides surgeons with a three-dimensional view of essential brain structures in real time, overcoming the limitations of traditional navigation systems and potentially improving surgical precision. In our case series involving five patients, we combined AR-based visualization with neurophysiological monitoring, allowing precise mapping of the corticospinal tract relative to the tumor. This approach contributed to complete tumor removal in most cases, while also preserving motor function in all patients. Our findings suggest that AR technology can enhance spatial understanding during complex surgeries, minimizing the risk to critical neural pathways. While our initial results are promising, demonstrating reliable alignment accuracy and improved outcomes, further studies on larger patient groups are necessary to fully understand and validate AR’s role in neurosurgery. This research underscores AR’s potential to improve both safety and outcomes, adding valuable tools for intraoperative navigation.
NGD-associated Ptolemeba bulliensis Watson et al., 2014 (Amoebozoa, Tubulinea) from rainbow trout (Oncorhynchus mykiss Walbaum, 1792) gills tolerates brackish water conditions up to 18 ppt
Authors: Kudryavtsev Alexander , Volkova Ekaterina , Parshukov Aleksey 
Published: December 2024

Abstract

We isolated a new strain of an amoebozoan, Ptolemeba bulliensis Watson et al., 2014 (Tubulinea) from the gills of farmed rainbow trout (Oncorhynchus mykiss Walbaum, 1792) showing signs of nodular gill disease. The studied strain can be identified using morphological and molecular (small subunit ribosomal RNA gene sequence data) characters. We obtained for the first time actin and cytochrome c oxidase (Cox1) gene sequences for this morphospecies. An interesting feature of the Cox1 gene is the presence of group I intron that contains a 177 amino acids long open reading frame encoding a homing endonuclease. This is the first case of a group I intron in the Cox1 gene in Amoebozoa apart from Dictyostelium. In experimental study, these amoebae demonstrate a broad range of salinity tolerance. They are capable of survival and reproduction in a range of salinities between freshwater Prescott and James medium and 18‰, but could not survive or reproduce in 25‰ and above. This indicates a possibility of this species’ distribution through brackish water biotopes, and shows that in case of pathogenicity for the farmed fish, the methods of treatment based on increasing salinity may be inefficient.
Tackling within-country spatial inequalities in household energy use towards sustainable development: The case of Ghana.
Authors: Nsenkyire Elizabeth , Nunoo Jacob , Sebu Joshua 
Published: December 2024

Abstract

Within-country spatial inequalities in accessibility and usage of modern energy and its services have been recognized by several studies globally. Despite this, studies that commit to analyzing and identifying ways to bridge these spatial disparities are scanty. Being a sub-Saharan African country with hyped improvement in energy access, other dimensions of household energy use deteriorate in Ghana, coupled with spatial inequalities within the country. This study, therefore, examined the socioeconomic drivers of the spatial disparities in household energy accessibility, utilization, and affordability between the three ecological zones of Ghana, as well as the rural and urban divide. Cross-sectional data from the latest Ghana Living Standard Survey (GLSS 7) was analyzed using the multidimensional energy poverty measure, the logit regression model, and the Oaxaca-Blinder decomposition for binary dependent models. The study found spatial differences in multidimensional energy poverty between the two geographical divides to be driven by socioeconomic characteristics such as education, location of residence, and income poverty. The study recommends that the socioeconomic characteristics of households be improved through programs and policies to alleviate the spatial inequalities in modern energy use within countries.
Explainable AI in brain tumor diagnosis: A critical review of ML and DL techniques
Authors: Kumar Krishan , Jyoti Kiran , Kumar Krishan 
Published: December 2024

Abstract

Brain tumors, caused by abnormal tissue growth within the brain, can severely disrupt brain functions and pose significant health risks. As the tumor progresses to higher stages, the patient's prognosis and survival decrease, resulting in a high mortality rate. With the advancements in medical imaging, especially the use of MRI, AI approaches have emerged as strong tools for detecting, segmenting, and classifying brain cancers. CNN and hybrid models, such as Vision Transformers (ViTs), have produced promising findings in this area. Although AI models exhibit high accuracy, they suffer from a lack of transparency and interpretability, paving the way for the development of eXplainable AI (XAI) methods in brain disease diagnosis. This paper investigates the utilization of machine learning, deep learning, and explainable AI (XAI) in brain tumor detection, segmentation, and classification. In this study, we have utilized the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist and diagram. Peer-reviewed articles from PubMed, IEEE Explore, ScienceDirect, Google Scholar, Springer, and Wilay online libraries were searched, and only those papers were selected that were published in Scopus, SCIE, and ESCI-indexed journals. We have identified the 20 research papers published between 2020 and 2024 that used machine learning, deep learning and explainable AI to detect, segment, and classify the brain tumor. This review provides a comprehensive survey the of explainable artificial intelligence (XAI) in biomedical imaging, focusing on its role in the detection, segmentation and classification of brain tumors. It examines various machine learning, deep learning and XAI techniques, addresses current challenges, and suggests future directions. The objective is to provide clinicians, regulators and AI developers with valuable insights to improve the transparency and reliability of these methods in medical diagnostics.
Optimized Soil Adjusted Vegetation Index Mapping of Pune District using Google Earth Engine
Authors: paul nobin chandra , Navyasree Ponnaganti 
Published: December 2024

Abstract

This article explores the application of the Optimized Soil Adjusted Vegetation Index in mapping the vegetation cover of Pune District using Google Earth Engine. The map has been generated using Google Earth Engine from MODIS products (MOD13Q1) over a 23-year period (2000-2022) at spatial and temporal resolutions of 250 meters and 16 days, respectively. By incorporating the soil-brightness correction factor, this index enhances the accuracy of vegetation assessments, particularly in regions with low vegetative cover or mixed land use. In the OSAVI map of Pune district, the values range from -0.048 to 0.455, where negative values indicate non-vegetated surfaces and higher values, observed in tehsils like Mulshi, Velhe, Maval, and Bhor, suggest dense and healthy vegetation. Validation of the generated map was carried out by using high-resolution Google Earth images. This validation process showcased the effectiveness of the generated map in accurately identifying vegetation patterns within the Pune district. The alignment of the map’s results with the patterns observed in the Google Earth images solidifies its accuracy and reliability. The generated map can be a valuable tool for monitoring land degradation, assessing crop health, detecting abiotic stress indicators, monitoring agricultural drought and studying vegetation dynamics in arid and semi-arid regions where soil brightness can significantly impact NDVI measurements. The implications of this work are significant. By enhancing vegetation assessment accuracy, it provides reliable tools for policymakers and environmental managers to monitor and manage natural resources.
A CULTURE OF HAPPINESS: EXPLORING THE RELATIONSHIP BETWEEN UNIVERSITY STUDENTS’ QUALITY OF LIFE AND ORGANIZATIONAL CULTURE IN HIGHER EDUCATION
Authors: Kerman Merve , Özdemir Murat 
Published: December 2024

Abstract

Various factors contributing to students’ quality of life in higher education have been researched in existing literature. Yet, the role of university culture on students’ quality of life in higher education is an underexplored area. In the present study, we aimed to investigate the relationships between students’ quality of life and university culture in Turkish higher education. The sample involved 617 undergraduate students studying in three privately funded foundation universities in Turkey. We used WHOQOL-BREF(TR) as an assessment tool to measure the four domains of quality of life (physical health, psychological, social relationships and environment). We used the Turkish version of OCAI instrument to measure university culture types (hierarchical, market and innovative team). Ordinal regression analysis was performed to determine the significant effects of university culture types on the domains of quality of life. This current study reveals novel findings about Turkish higher education. Results demonstrate that innovative team culture affects the psychological and social relations domains of students’ quality of life positively. One interesting finding is that positive correlation was identified between market culture and the physical health domain of QoL. In addition, we found economic status and gender to be significant predictors of students’ quality of life. This current research provides university authorities and policy makers with an in-depth analysis for informed decision making and constructive strategy planning. It also presents an analysis of the quality of life of university students to inform future studies in higher education policy and management.
Median Based Unit Weibull Distribution (MBUW): Does the Higher Order Probability Weighted Moments (PWM) Add More Information over the Lower Order PWM in Parameter Estimation
Authors: Attia Iman Mohammed 
Published: December 2024

Abstract

In the present paper, Probability weighted moments (PWMs) method for parameter estimation of the median based unit weibull (MBUW) distribution is discussed. The most widely used first order PWMs is compared with the higher order PWMs for parameter estimation of (MBUW) distribution. Asymptotic distribution of this PWM estimator is derived. This comparison is illustrated using real data analysis.
Curcumin Nanoparticles: Exploring Types and their Impact on Biopharmaceutical Performance
Authors: Gauniya Priyanka , Radheshyam . , Semalty Ajay , Semalty Mona 
Published: December 2024

Abstract:
Turmeric (Curcuma longa) contains a polyphenol called curcumin, which has a variety of
medicinal uses, including anti-inflammatory, antioxidant, and anticancer effects. However, due to its
rapid disintegration, low solubility, and poor absorption, its clinical application is restricted. To
overcome these challenges, researchers are exploring the use of various kind of curcumin nanoparticles,
which enhance its solubility, stability, and bioavailability to deliver its benefits more efficiently.
Integrating curcumin into composite nanoparticles has emerged as a prominent strategy to overcome
the limitations of curcumin’s bioavailability. This review aims to overview various curcumin
nanoparticle forms that have been synthesized to enhance curcumin's permeability, solubility, and
oral bioavailability. Specifically, we explored polymeric nanoparticles, lipid nanoparticles, nonpolymeric
nanoparticles, and nanocrystals as carriers to enhance the biopharmaceutical properties of
curcumin. The collected data from the literature indicated significant improvements in solubility and
permeability, with lipid-based and polymeric nanoparticles showing the most promising results in
enhancing the oral bioavailability of curcumin. It can be suggested that nano encapsulation not only
protects curcumin from rapid degradation but also facilitates its efficient transport and absorption at
target sites.
A Biodegradable and Biocompatible Dental Hemostatic Gelatin Sponge Containing Aloe Vera Nanoparticles; Investigation in Rat Animal Model
Authors: Khosroshahi Ali Zaheri , Ghavimi Mohammad Ali , Sharifi Simin , Vazirabadi Samin Baghban , Deljavanghodrati Tara , Dizaj Solmaz Maleki 
Published: December 2024

Introduction:
A variety of hemostatic materials have been provided to accelerate the
blood clotting process in dentistry. The purpose of this study was to investigate the biocompatibility
and biodegradability of a hemostatic dental sponge containing aloe vera nanoparticles in rat animal
models.

Methods and Materials:
Twelve adult Wistar rats in the weight range of 200 ± 30 grams and the
same age range were randomly divided into two groups of test and control, and each group was divided
into three subgroups of 3 days, 7 days, and 14 days. For implantation of the sponge, the animals
were anesthetized with xylazine and ketamine, and a piece of the sponge was implanted under
the skin at the cut site. In the control group of rats, only the skin was cut and sutured. After the
specified number of days, the rats were anesthetized, and in addition to blood sampling, a tissue
sample was taken from the animal's surgical site and fixed in 10% formalin. Then the samples
were examined in macroscopic and microscopic conditions and finally, the obtained data were statistically
analyzed.

Results:
The results obtained in the present study indicated that the hemostat sponge had no side
effects (biocompatible). In addition, it was completely absorbed during the 14 days of the study
(biodegradable).

Conclusion:
According to the characteristics of biocompatibility and biodegradability, the studied
sponge can be used to control bleeding during dental surgeries or tooth extraction.