bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bioactive potential of polysaccharides produced by lactic acid bacteria
Authors: Amin Shimaa A. , Radwa E. Noureldein , Refaat A. A , El-Dougdoug K.A ,   Khadiga, A. Abou-Taleb1
Published: November 2024

Abstract

Lactic acid bacteria (LAB) have attracted considerable attention because of their ability to generate exopolysaccharides (EPS).Exopolysaccharides play a crucial role in human health, demonstrating notable antitumor, antioxidant, and antimicrobial properties. This study aimed to optimize the production of EPS by lactic acid bacteria LAB isolates and evaluate their bioactivities.LAB isolates were screened for EPS production under different culture conditions. Twenty isolates with promising bioactivities were selected and further studied. The best isolate was analyzed for total sugar content and its potential as an anticancer and antiviral agent. LAB cultures showed an increase in EPS production in modified MRS medium with an initial pH of 6.8 and 37 °C. The dry polymer weight (DPW) and viscosity of EPS varied between 1500 and 17500 mg/ll, with the K1 isolate exhibiting the highest DPW. EPS exhibited notable antioxidant and antibacterial properties, with CH3, P2 and P4 showing significant bioactivity. The CH3 isolate, identified as Lactobacillus brevis, producing EPS in sweet whey medium,exhibited potential anticancer effects against Caco-2 cells and antiviral activity against HAV. The dry polymer and viscosity did not show significant differences between isolates and conditions. In summary, EPS exhibits antioxidant, antimicrobial,anticancer, and antiviral properties, suggesting potential applications in the food industry and for human health.
Effectiveness and sequencing of water, sanitation and hygiene interventions to reduce mortality in childhood: a multicomponent network meta-analysis
Authors: Masset Edoardo , Waddington Hugh Sharma 
Published: November 2024

Abstract

Mortality in childhood constitutes the vast majority of the global burden of disease due to diarrhoea and respiratory infection. We employ a multi-component network meta-analysis to evaluate the comparative effectiveness of WASH interventions implemented as stand-alone interventions or as multicomponent intervention packages, in reducing all-cause mortality in childhood in endemic disease circumstances in low- and middle-income countries. We find that interventions providing water supplies are most consistently associated with reductions in all-cause mortality in childhood. Furthermore, when initial water supplies are improved, hygiene and sanitation interventions are also more effective. However, we find that behaviour change WASH intervention packages are less effective than stand-alone interventions and that there are no synergies between interventions. These findings caution against the implementation of multicomponent behavioural intervention packages and favour prioritising approaches that improve water supply conditions first. We highlight conflicting behavioural change as a potential cause of the absence of synergies in WASH intervention packages.
Enhancing youth motivation for STEM through Tiny house construction projects.
Authors: Kegels Christophe , Thomas Valérie 
Published: November 2024

Abstract

This research aimed to gain insight into the impact of motivational interventions on adolescents' motivation for STEM activities in an extracurricular project. The participants in this project were twelve adolescents with a minimum age of fourteen. A qualitative data collection method was used using semi-structured interviews. These interviews were analyzed using a combined thematic data analysis to understand the impact of motivational interventions on participants' motivation. The data collection took place during the Growth House project. The results showed that motivational interventions applied in school contexts, such as those based on the self-determination theory and Achievement Goal Theory, positively influenced the motivation of the participating adolescents. The participants indicated that, while facilitators were effective in many aspects, there was still room for improvement in certain areas. These findings can be utilized by the facilitators of the Growth House project to better address participants' motivation for future projects. From a policy perspective, these results suggest that extracurricular projects are a promising strategy for motivating young people in STEM activities. Further research should investigate whether these findings can be generalized to the broader adolescent population and explore whether extracurricular STEM projects contribute to an increase in young people pursuing STEM education.
Allocation of Lineaments Based on a Digital Model of the Bottom Relief on the Example of the Caspian Sea
Authors: Libina Natalia , Putans Victoria , Kovachev Sergey 
Published: November 2024

Abstract

This work is devotedto aspects of the application of morphometric methods of analyzinga digital model of the bottom relief for the allocation of regional scale elements on the exampleof the Caspian region. The study showed that the combined useof geomorphometric analysis methods, in particular shadow analysis and keel shape extraction by calculatingthe curvature of the relief, with data onthe distribution of earthquake epicentersmakes it possible to identify active fault zones and may prove very promising in assessing seismic hazards onthe shelf.
Divergence of discrete- versus continuous-time calculations of the temperature dependence of maximum population growth rate
Authors: Huxley Paul , Johnson Leah , Cator Lauren , Pawar Samraat 
Published: November 2024

Abstract

The temperature dependence of population fitness (rm) is key to predicting ectotherm responses to climatic change. Discrete-time matrix projection models (MPMs) are used to calculate rm because they capture variation in its underlying life-history trait values and time delays inherent in those traits. However, MPM calculations can be laborious and do not capture time’s continuous nature. More complex approaches for calculating temperature-dependent rm may be more accurate but they are notoriously difficult to parameterise. Ordinary differential equation-based models (ODEMs) offer a relatively tractable alternative of intermediate complexity, but it is unknown whether they broadly agree with MPM calculations when environmental variation is introduced. Here we investigate differences in the predicted temperature dependence of rm obtained from an ODEM with those calculated from MPMs using temperature- and resource dependent life-history trait data for the disease vector, Aedes aegypti. We show that the level of agreement between discrete- and continuous-time representations of temperature-dependent rm can vary with resource availability and is extremely sensitive to juvenile survival characterisations. This finding suggests that ODEMs can only provide comparable rm predictions to standard methods when resources are not limiting, questioning the ability of existing mathematical models to reliably predict arthropod responses to environmental variation.
Clustering and Seasonal Variability of Weak Seismicity in the Lena Delta (Laptev Sea Region)
Authors: Novikov M. A. , Krylov A. A. , Radyuk E.A. , Geissler W.H. , Krüger F. , Baranov B. V. , Tsukanov N.V. , Shibaev S.V. 
Published: November 2024

Abstract

The present work is devoted to studying the characteristics of the spatiotemporal microearthquake distribution in the Lena Delta using data from local seismological monitoring conducted from 2016 to 2018. The results revealed the confinement of microearthquake sources to the Olenek segment of the Lena–Taimyr zone of boundary uplifts, marking the boundary of the Siberian Platform and the Laptev Sea Rift System. The Olenek segment fault zone is traced by hypocenters up to the Moho at a depth of about 40 km. Microearthquakes are distributed unevenly in both space and time, forming clusters in different parts of the fault zone. These clusters can be interpreted as originating from unstable stick-slip sliding during the process of background stable creeping. Seasonal variability in the number of recorded weak earthquakes in the Lena Delta has been revealed. An extended regional catalog (2003–2022) was also used to analyze the seasonal seismicity modulation. The average number of events per day increases by approximately a factor of two during cold seasons. Comparison of these results with snow cover thickness, the Lena water level, GNSS data, gravity data, and calculated additional Coulomb stresses revealed that the seasonal seismicity increase in the Lena Delta correlates with the positive additional Coulomb stresses under conditions of prevalence of normal faults in the Olenek segment. Additional Coulomb stress directly depends on equivalent water thickness, which, in turn, correlates with snow cover thickness. The summer flood does not have a significant impact on the seismicity rate, presumably due to its short duration.
Standardizing Free-Text Data Exemplified by Age and Data-Location Fields in the Immune Epitope Database
Authors: Duesing Sebastian , Bennett Jason , Overton James A. , Vita Randi , Peters Bjoern 
Published: November 2024

Abstract

Background
While unstructured data, such as free text, constitutes a large amount of publicly available biomedical data, it is underutilized in automated analyses due to the difficulty of extracting meaning from it. Normalizing free-text data, i.e., removing inessential variance, enables the use of structured vocabularies like ontologies to represent the data and allow for harmonized queries over it. This paper presents an adaptable tool for free-text normalization and an evaluation of the application of this tool to two different sets of unstructured biomedical data curated from the literature in the Immune Epitope Database (IEDB): age and data-location.
Results
Free text entries for the database fields for subject age (4095 distinct values) and publication data-location (251,810 distinct values) in the IEDB were analyzed. Normalization was performed in three steps, namely character normalization, word normalization, and phrase normalization, using generalizable rules developed and applied with the tool presented in this manuscript. For the age dataset, in the character stage, the application of 21 rules resulted in 99.97% output validity; in the word stage, the application of 94 rules resulted in 98.06% output validity; and in the phrase stage, the application of 16 rules resulted in 83.81% output validity. For the data-location dataset, in the character stage, the application of 39 rules resulted in 99.99% output validity; in the word stage, the application of 187 rules resulted in 98.46% output validity; and in the phrase stage, the application of 12 rules resulted in 97.95% output validity.
Conclusions
We developed a generalizable approach for normalization of free text as found in database fields with content on a specific topic. Creating and testing the rules took a one-time effort for a given field that can now be applied to data as it is being curated. The standardization achieved in two datasets tested produces significantly reduced variance in the content which enhances the findability and usability of that data, chiefly by improving search functionality and enabling linkages with formal ontologies.
Unveiling the Hidden Link: Stomach Disease as a Risk Factor for Knee Osteoarthritis
Authors: Yang Xing , Yang Xi , Li Ping , Liu Hong 
Published: November 2024

Abstract

Background
The knee joint is one of the most frequently affected joints in osteoarthritis (OA). However, the specific connection between gastric diseases and the occurrence of knee osteoarthritis (KOA) is currently unclear. The objective of this study is to explore the potential association between gastric diseases and KOA using the China Health and Retirement Longitudinal Study (CHARLS) database.
Methods
A total of 1053 subjects with complete information in 2018 from CHARLS database were included. First, the baseline characteristics of these subjects (covariates such as gender, residence, and smoke) were compared. Then, the relationship between stomach diseases and KOA was explored through 3 weighted multivariate logistic regression models. Afterwards, risk stratification analyses were taken to further confirm the stability of the correlation between stomach disease and KOA risk in different populations. The receiver operating characteristic (ROC) curve of model 3 was plotted to verify the predictive efficiency of stomach disease in KOA risk.
Results
we divided the subjects into 2 groups: the KOA group (n = 71) and the control group (n = 982). The baseline characteristics table revealed that substantial differences in heart attack, kidney illness, stomach disease, as well as health status between the KOA and control groups. Model 1 had an odds ratio (OR) of 3.05 (95% confidence interval (CI) = 1.75–5.30, P < 0.001). After adjusting for location, gender, and smoke, model 2's OR was 3.02 (95% CI = 1.73–5.28, P < 0.001), while model 3's OR was 2.48 (95% CI = 1.37–4.47, P = 0.002). The 3 models demonstrated that stomach disease and KOA were significantly associated and stomach disease was a risk factor for KOA, and the other covariates did not change the relationship. Risk stratification analyses indicated a stable association between stomach disease and KOA risk across populations. The area under the curve (AUC) was 0.722, indicating that model 3 had a good predictive accuracy.
Conclusion
In this study, we furtherly explored the correlation between stomach disease and KOA, and certified that stomach disease was a risk factor for KOA, which provided a reference for the correlation analysis between them.
Modelling, Parametrizing and Simulating a DEM-Based Soil-Model for Industrial Applications
Authors: Emmerich Sebastian , Franosch Georg , Burger Michael , Ullrich Anita , Quist Johannes 
Published: November 2024

Abstract

Simulation and simulation-assisted methods have a large impact for product development in many industrial fields. Multibody dynamics (MBD) simulation, for instance, is an established method used for durability analysis and energy efficiency calculations in vehicle engineering, based on its ability to provide accurate prediction of interaction forces. In the domain of off-road vehicles and heavy machinery, such considerations need to be expanded by a method to model the soil and its interaction with the vehicle, i.e., the soil-tool interaction, as the resulting forces may drastically influence the durability and energy efficiency of the machine. Therefore, the model must be chosen carefully to maintain the high accuracy in the force prediction for the soil-tool interaction, as required for a reliable and robust product development.
In this contribution, we present a workflow to tackle this topic, based on a co-simulation scheme between an MBD-based vehicle model and a particle simulation realized in the Discrete Element Method (DEM). The simulated soil is parametrized and validated by matching simulation results from a virtual experiment with measurement data from real-world soil laboratory experiments as the triaxial compression test. Using this process, the applicability and performance of the numerical methods can be determined.
Mapping Connective Tissue Molecular Blueprints to Illuminate Human Keratinized and Non-Keratinized Oral Mucosa
Authors: Chen Shoucheng , Huang Ruoxuan , Xu Leyao , Xu Chunxin , Liu Yuanxiang , Liu Runheng , Deng Shudan , Li Zhipeng , Chen Zetao , Chen Zhuofan 
Published: November 2024

Abstract

A fundamental question in oral science is elucidating the factors that underpin the distinct tissue characteristics of human keratinized and non-keratinized mucosa. Clinical autotransplantation and large animal studies have observed that intrinsic regulation within connective tissue defines mucosal phenotypes, emphasizing the need for in-depth molecular characterization, which remains largely unexplored. This study aimed to map the molecular blueprints of in situ connective tissues and isolated fibroblasts of human keratinized oral mucosa (gingiva, GIN) and non-keratinized oral mucosa (alveolar mucosa, ALV). Distinct variations were observed in extracellular matrix composition, retinoic acid metabolism (closely associated with keratinization), and immune function between GIN and ALV. GIN displayed higher expression of collagen-related genes (notably COL1 and COL3) and lower expression of elastin-related genes. In GIN, the retinol metabolism pathway was enriched, with downregulation of retinoic acid synthesis and upregulation of its catabolism. In contrast, the complement and coagulation cascade were notably upregulated in ALV, with significantly elevated expression of C3. This study is the first to systematically dissect and compare the molecular profiles of connective tissue in GIN and ALV providing foundational insights that could drive future advancements in mucosal phenotype modulation and regenerative therapies.
Performance Analysis of Multiple Delayed Signal Cancellation (MDSC) for Power Quality Improvement for Fixed Speed SEIG-Based Distributed Generation
Authors: Shailly Divyansh , Chittora Prakash , Singh Madhusudan 
Published: November 2024

Abstract

The proposed work described a new Multiple Delay Signal Cancellation (MDSC) control technique for power quality improvement including harmonic cancellation and power factor improvement for a three-phase self-excited induction generator (SEIG)-Distributed Static Compensator (DSTATCOM) based system. A detailed design and stability analysis is being carried out. The MDSC possesses multiple variable length delay signals so as to extract the positive and the negative sequence components (PSC and NSC) so as to generate sinusoidal reference currents for the source. An extensive simulation analysis is being executed to illustrate the controller's efficiency using MATLAB/SIMULINK. A hardware prototype is being developed in the laboratory including SEIG and DSTATCOM. The hardware results prove the effectiveness of the proposed control filter.
Integrated organic geochemical and palynological study of Eocene Kopili Shale in North Cachar Hills, Assam, India: Source rock potential, depositional environment and paleoclimate implications
Authors: Mout Joya Moni , Sarmah Ranjan Kumar , Gogoi Nababrot 
Published: November 2024

Abstract

We conducted this first-ever integrated organic geochemical and palynological study of the Kopili Shale (KS) in North Cachar Hills (NCHs) of Assam, India, aiming to assess its source rock potential, depositional environment and palaeoclimate conditions. Organic geochemical study reveals that majority of the samples exhibit low total organic carbon content (TOC) (0.11–1.83 wt. %; average: 0.5%), implying poor hydrocarbon source potential. S1 (0.01–0.11 mg HC/g rock; average: 0.03 mg HC/g rock) and S2 (0.04–3.51 mg HC/g rock; average: 0.36 mg HC/g rock) contents are poor, which indicate poor source rock quality. Low Genetic potential (GP) values (0.05–3.62 mg HC/g, average: 0.39 mg HC/g) suggest poor, gas/non generative source rock. The samples contain terrigenous organic matter (OM) with predominant type III (gas-prone) and IV (inert) kerogen, hence are expected to produce gas, or the kerogens are inert or thermally overmature. Tmax values (370–471°C) imply thermally immature to post-mature source rock. Our current organic geochemical study divulges that the KS in the NCHs has poor source rock potential for producing hydrocarbon. Regionally, the source rock potential of the KS in the NCHs aligns with those found in the contiguous surface regions, the Shillong Plateau (SP), Meghalaya, and in Bengal Basin (BB), Bangladesh. Conversely, KS in the subcrops of the Upper Assam Shelf (UAS) has fair to good potential for producing hydrocarbon. Comprehensive palynological study discloses that the KS in the NCHs, adjacent areas, sub crops of UAS, SP, and BB was deposited in a shallow marine environment (SME) under suboxic - anoxic basin (SAB) conditions. The paleoclimate during deposition of the KS was tropical - subtropical (TST) with warm - humid (WH) palaeoclimatic condition. This pioneering investigation can guide future exploration in larger areas including contiguous surface as well as subsurface regions. This analysis is crucial for companies in the energy sector to optimize extraction techniques and manage resources efficiently.
Association of New Inflammatory Markers Cumulative Inflammatory Index (ICC) and Mean Corpuscular Volume/Lymphocyte (MCVL) with Anti PD-1 Antibody Nivolumab Treatment Response in Metastatic Renal Cell Carcinoma
Authors: SURMELI Heves , ISIK Deniz , BAL Hamit , TUNBEKICI Salih , KINIKOGLU Oguzcan , ALTINTAS Yunus Emre , AKDAG Goncagul , YILDIRIM Sedat 
Published: November 2024

Abstract

Introduction: Kidney cancer is an immunogenic tumor and inflammation plays a role in tumor formation and progression. The aim of this study was to investigate the effect of biochemical markers in predicting treatment response in patients with metastatic renal cell carcinoma (RCC) receiving nivolumab treatment.
Method: Patients aged ≥18 years who received nivolumab treatment for metastatic RCC between February 2022 and January 2024 were evaluated. Cellular blood count was evaluated at the diagnosis of metastatic disease and periodically during nivolumab treatment. We measured the cell count in peripheral blood at admission and calculated the inflammation indices obtained from the blood cell count as follows: MCVL (mean corpuscular volume/lymphocytes) and IIC ((mean corpuscular volume * width of erythrocyte distribution * neutrophils / (lymphocytes*1000)).
Results: The study included 99 patients. The mean age of the patients was 58.32±11.95 (19-87). 75.8% of the patients had clear cell and 8.1% had papillary type pathology. When the disease control status was evaluated at 3 months after nivolumab treatment, it was seen that 48 patients had partial response and 18 patients remained stable. The 3rd month disease control rate (DCR) was 68.7%. When the ICIC and MCVL rates of the patients were examined, it was determined that the ICC and MCVL values of the patients who showed progression were higher (p=0.038 for ICC, p=0.040 for MCVL). The ICC cutoff value was determined as 15.50. With this cutoff value, disease control can be predicted with 77% sensitivity and 64% specificity (AUC: 0.743 CI 95% [0.647-0.838]; p<0.001). MCVL cutoff value was determined as 65.15. This cutoff value can predict disease control with 65% sensitivity and 61% specificity (AUC: 0.674, CI95% [0.564-0.783], p=0.006).
Conclusion: ICC and MCVL have a significant effect on disease-free survival and overall survival in predicting success of nivolumab treatment for metastatic renal cell carcinoma.
Predicting the Risk of Surgical Complications Using Machine Learning Models
Authors: Santos Dheiver Francisco 
Published: November 2024

Abstract

Predicting the risk of surgical complications is essential to improve patient outcomes and optimize healthcare resources. In this paper, we propose the application of machine learning (ML) techniques to predict surgical risks based on pre-operative data. We used three supervised learning algorithms: Logistic Regression (LR), Random Forest (RF), and Support
Vector Machine (SVM). A stacked ensemble model combining these algorithms was also explored to enhance the prediction accuracy. The proposed ensemble model achieved a prediction accuracy of 94