bluuebunny/crossref_metadata_2025_split huggingface dataset:
WITHDRAWN: Designing a Nature Play Module for Preschool Teachers Using the Fuzzy Delphi Method: A Structured Approach for Early Childhood Education
Authors: Yanfei Xu , Rahman Mohd Nazri Abdul 
Published: November 2024

Abstract

The integration of nature play into preschool education has gained increasing attention due to its positive impact on children's development. However, many preschool teachers face challenges in implementing nature play effectively. This study aims to develop a Nature Play Module (NPM) to provide systematic guidance for teachers, enhancing their ability to integrate nature play into their curriculum and support children's holistic growth within the Chinese context. Using the Fuzzy Delphi Method (FDM), this research engaged 12 experts, including 4 specialists in early childhood education, 4 kindergarten principals, and 4 preschool teachers, in two rounds of surveys, utilizing semi-structured interviews and questionnaires. Data analysis results showed that the experts accepted all these elements through the expert consensus value above 75%, the threshold value (d) ≤ 0.2, and the fuzzy score (A) ≥ α - cut value = 0.5. The resulting module comprises 10 key themes and 61 sub-themes, which include the objectives, principles, teaching strategies, frequency and duration, environment and venue, activity resources, activity process, activity evaluation, precautions.
Depollution of water contaminated by Yellow Bezacryl (YB) - Kinetic study, Isotherms modeling and Adsorption Mechanism.
Authors: ABBAS Moussa 
Published: November 2024

Abstract

Progress in industrial and agricultural activities, as well as the discharge of insufficiently treated effluents, notably dyes and heavy metals, have amplified the polluting load on the environment. These organic compounds pose considerable challenges in drinking water and wastewater treatment systems, given their toxicity, high oxygen demand, and limited biodegradability climate change poses a threat to water security by altering precipitation patterns and other weather variables, which affect river flow and freshwater availability. This study is focused on the application of adsorption and photocatalysis of the Yellow Bezacryl (YB) dye in the presence of typical TiO2 (Eg = 3.5 eV) semiconductor and suggests a likely mechanism for this process. For that the effects of contact time, initial pH, adsorbent dosage and YB initial concentration on the dye adsorption by TiO2 catalyst have been studied. The adsorption of YB onto TiO2 catalyst has been investigated at batch conditions. The adsorption mechanism of YB onto TiO2 catalyst was studied by using the First-pseudo order, Second-pseudo order models. The adsorptions kinetics were found to follow rather a pseudo-second order kinetic with a determination coefficient (0.9906 < R2 <0.9968). The adsorption isotherm is a mathematical model that relates the equilibrium amount of the adsorbate immobilized onto the adsorbent surface to those remaining in the solution. Several models Langmuir, Freundlich, Temkin and Elovich models have been documented for describing the experimental data obtained for the adsorption processes. The adsorption follows well the Langmuir equation, providing a better fit of the equilibrium adsorption data (R2 = 0.998, SSE = 0.0006). Under optimized conditions, up to 14.705 mg/g at 25 oC is removed from the solution. The experimental results showed that the efficiency of the photocatalytic process strongly depends on the pH while the initial rate of the photocatalytic reaction is proportional to the catalyst dose, but above a certain value it becomes constant and sometimes decreases. The adsorption is an important parameter controlling the apparent kinetic constant of the degradation. The photocatalytic degradation rate was favored for high concentrations of solution in agreement with Langmuir–Hinshelwood (L-H) model. The values kc and K for the photocatalytic degradation of YB were found to be 1.992 mgL/min and 0.2906 L/mg respectively. The degradation rate was found to be dependent on pH and temperature with a high degradation rate for pH 4 and a rise in temperature. The TiO2 catalyst has a better activity for the YB degradation, compared to the various commercial catalysts already available in the literature.
Navigating condensate microenvironment to enhance small molecule drug targeting
Authors: Li Tingting , Zhang Xin , Ouyang Jian , Chen Junlin , Wu Zhili , You Kaiqiang , Chen Taoyu , Gao Yi Qin , Li Pilong 
Published: November 2024

Abstract

Many pharmaceutical targets partition into biomolecular condensates, whose microenvironment could significantly influence drug distribution. Nevertheless, it's unclear how small molecule drug design principles should adjust for these partitioned proteins to optimize target engagement. Here, we address this question by systematically investigating how the condensate microenvironment influences drug targeting efficiency. We found condensates formed by intrinsically disordered regions with varying properties highlighted a notable heterogeneity, with nonpolar residue-enriched condensates being more hydrophobic and housing more hydrophobic drugs and endogenous metabolites. Further, the L1000 dataset analysis revealed a strong positive correlation between inhibitor hydrophobicity and targeting efficiency for phase-separated (PS) proteins, represented by ESR1 enriched with nonpolar residues. In cellulo experiments with ESR1 condensates confirmed that both binding affinity and hydrophobicity contribute significantly to enhancing inhibitor potency. These results suggest a new drug design principle for PS proteins by considering condensate microenvironments, potentially leading to more effective drugs that exhibit optimal target engagement.
Does a Gentamicin-coated intramedullary nail prevent postoperative infection in Gustilo Type I and II tibial open fractures? A comparative study and retrospective analysis .
Authors: Rai SK , Gupta TP , Kashid Manoj , Sirohi Bhavya , Kale Amit , Sharma Ritesh 
Published: November 2024

Abstract

Purpose
Tibial open shaft fractures are very common and susceptible to infection, which can lead to significant morbidity especially infection and non-union. Antibiotic coated nail is one option for fixing open shaft tibial fractures to minimise infection. This study aimed to compare the clinical outcome of Gentamicin-coated tibial nails versus regular unreamed interlocking tibial nails in the treatment of type I and II tibial open fractures.
Methods
In the present study of 124 patients with Gustilo type I and II tibial fractures, 62 patients were treated with non-antibiotic-coated regular nails (control group, Group A), and 62 patients were treated with Gentamicin-coated nails (study group, Group B). They were followed for 12 months for fracture union. Fracture union was assessed by The Radiographic Union Scale for Tibial fractures (RUST) criteria.
Results
The postoperative infection rate in the regular nail group was 9.6% (6/62 patients), whereas it was 3.2% (2/62 patients) in the antibiotic nail group (χ2 = 4.64\chi^2 = 4.64χ2 = 4.64, p = 0.031p = 0.031p = 0.031). The Gentamicin-coated nail group showed a better fracture union rate compared to the regular nail group at the 6-month and 12-month follow-ups (p = 0.0267p = 0.0267p = 0.0267).
Conclusion
A tibial nail coated with Gentamicin is an effective method for preventing infection in type I and II open fracture shafts of the tibia. It allows, shortens hospital stay and healing time, prevents infection, and thus reduces the chance of a second surgery.
Level of Evidence
Level III, a prospective study
Glomerular filtration rate in children with sickle cell disease in the Eastern Region of Saudi Arabia
Authors: Zayed Abdalla Mohamed , Zayed Abdalla , Almohaimeed S , Eltayeb A , Alharbi R , Alotaibi T , Aldosari H , Alotaibi TS , Awadallah Y , Ancheta SJ , Alasmari M , Algarni A , Alghamdi A , Abdulrahman R Al 
Published: November 2024

Abstract

Introduction
Sickle cell nephropathy (SCN) is a serious complication of SCD that starts insidiously in childhood, with possible progression to chronic kidney disease in adulthood. Our aim was to study the prevalence and clinical correlates of the glomerular filtration rate, the earliest marker of renal dysfunction, in the Eastern Region of Saudi Arabia (SA).
Methods
A retrospective cross-sectional study was performed on 114 Saudi children with SCD aged 1-14 years who attended the pediatric hematology clinic in a steady state. Renal function was evaluated via estimated glomerular filtration rate (eGFR). The prevalence of GHF, and the correlation of eGFR with different clinical and laboratory data were investigated. Moreover, a comparison of the clinical characteristics and eGFRs was performed between children from the Southwestern (SW) and Eastern regions of Saudi Arabia (SA) and living in the same Eastern environment.
Results
A total of 114 children with SCD were included in the study (Male to female ratio: 1.3:1). The mean age was 8.8 ± 3.2 years. They were divided into two groups based on their provenance: Eastern (n: 26/114) and SW (n: 88/114). The mean eGFR was 179.4±52.7 ml/min/1.73 m2 with a glomerular hyperfiltration (GHF) prevalence of (44.7%). There was no statistical difference between the two groups in terms of the mean GFR or prevalence of GHF (p>0.5). The eGFR correlated with hemolytic markers, including steady-state hemoglobin (HB) (r = −0.25, P 0.003), hematocrit (r=-0.27, p 0.002), HBF (r=-0.28, p 0.001), reticulocytes% (r=0.225, p 0.016), AST(r = 0.32, p   0.000), LDH (r=0.30, p 0.001)and bilirubin (r=0.317, p O.001). In the multivariate regression of the factors determining the eGFR at 95% confidence intervals, only HBF (β =0.216, P = 0.042) remained independently predictive (R2 = 0.197, p= 0.001). There was no correlation between the GFR and patient age, BP, WBC or platelet count.
Conclusion:
The prevalence of GHF among Saudi children with SCD in the Eastern region is high, with no significant difference between Eastern and SW patients. The eGFR was correlated with the hemolytic markers, and low HBF was predictive of GHF. Further studies are needed to validate these findings.
Investigating the Amorphous to Crystalline Phase Transition in Se 80 In 5 Te 15-x Bi x Chalcogenide Thin Films
Authors: Khan Imtiyaz H. , Tripathi Ravi P. , Akhtar M. Shaheer , Khan Zubair M. S. H. , Kim Chong Yeal , Khan Shamshad A. 
Published: November 2024

Abstract

This work pronounces the interchange from amorphous to crystallization phase in quaternary Se80In5Te15 − xBix chalcogenide thin films which was prepared by controllable melt quenching technique using a vacuum of 10− 5 Torr. Non-isothermal behaviour by DSC measurements was carried out to establish the amorphous as well as glassy state of the synthesized Se80In5Te15 − xBix alloys. For phase transformation, Se80In5Te15 − xBix chalcogenide thin films were performed by thermal annealing at different temperatures 343 K, 353 K and 363 K for 2 h followed by taking XRD (X- Ray diffraction) and FESEM measurements. After thermal annealing, Se80In5Te15 − xBix thin films were considerably transformed from amorphous to crystalline nature. The luminescence peak position with elevated intensity was slightly shifted when the annealing temperatures were increased. The annealed Se80In5Te15 − xBix thin films exhibited the increased absorption coefficients (α) and extinction coefficient (k) with decreased optical band gap when annealing temperatures were increased. The lowering in the optical band gap with temperature of annealing was described on the basis of transferred phase from amorphous to crystalline.
Does Poverty Alleviation Relocation Improve the Happiness of Rural Residents in China? Evidence from the Microdata of CHFS
Authors: Han Xueying , Han Xia 
Published: November 2024

Abstract

Drawing data from the 2019 China Household Finance Survey (CHFS), this article explores whether the relocation policy for poverty alleviation improves the happiness of rural residents in China. This study documents a significantly positive relationship between the relocation policy for poverty alleviation and the happiness of relocated rural residents. Furthermore, resident income is found to play a mediating role. Further heterogeneous analyses provide evidence of differences in policy effects for relocated people of different ages and regions. In order to avoid endogeneity, this articleselects the resident location as the instrumental variable, and the endogeneity test further verifies that the implementation of PAR can significantly improve the happiness of rural residents.The findings could help provide policy implications for follow-up assistance and grassroots governance in the relocation areas.
Enhancing Enzyme Activity with Mutation Combinations Guided by Few-shot Learning and Causal Inference
Authors: Tian Boxue , Guo Lin , Yan Xiaoguang , Nie Shengxin , Ge Mingyue , Li Yukun , Lu Yali , Li Weiguo , Zhang Xiaochun , Liang Dongmei , Zhao Yihan , Tan Hongxiao , Chen Xiling , Fan Shilong , Tang Yefeng , Qiao Jianjun 
Published: November 2024

Abstract

Designing enzyme sequences to enhance product yield represents a fundamental challenge in metabolic engineering. Here, we established a workflow that integrates computational predictions with efficient experimental iteration to obtain outsized gains in product yield. Based on causal inference and examination of published datasets from previous yield-boosting engineering efforts, we realized and ultimately experimentally confirmed that in vivo unit yield (yield/expression) can serve as an attractive surrogate for aqueous Kcat/KM when optimizing for in vivo enzyme activity. In our workflow, we initially predict activity-enhancing single mutants by calculating the binding affinities of reactive intermediates, followed by experimental investigations of unit yield. Subsequently, we predict activity-enhancing mutation combinations using a few-shot learning model we developed called Physics-Inspired Feature Selection of Protein Language Models (PIFS-PLM), which requires only 60–100 experimentally examined mutation combinations as input, and which identifies enzyme regions likely to support additional yield gains from mutation based on the “local activity landscape”. In a case study of a bicyclogermacrene (BCG) synthase, we achieve a 72-fold increase in BCG yield based on combinations of 12 individual mutations, and provide extensive crystallographic and biochemical evidence for impacts from specific mutations. Thus, optimizing for unit yield is highly efficient as an alternative to optimizing for thermostability, and our study provides a powerful workflow for the efficient engineering of high-yield enzyme variants.
Impact of Declared Wildfire Disasters on Survival of Lung Cancer Patients Undergoing Radiation
Authors: Lichter Katie E. , Larson Bria , Pagadala Meghana , Mohamad Osama , Nogueira Leticia 
Published: November 2024

Abstract

Purpose
Oncological treatments, such as radiotherapy, which requires consistent electricity, the presence of specialized clinical teams, and daily patient access to treatment facilities, are frequently disrupted by extreme weather events, posing several health hazards to patients [1–3]. This study explores the association between declared wildfire disasters during radiotherapy and overall survival among patients with non-small cell lung cancer (NSCLC).
Methods
The study population consisted of 202,935 adults with inoperable Stage III NSCLC, who initiated radiotherapy from 2004 through 2019. Exposure was defined as a wildfire disaster declaration in the county of the treatment facility within 12 weeks of initiating radiotherapy. Overall survival was defined as the interval (months) between age at diagnosis and age at death, date of last contact, or study end. Cox proportional hazards was used to estimate crude and adjusted hazard ratios and 95% confidence intervals with inverse probability weighting.
Results
Patients exposed to a wildfire disaster declaration during radiation treatment had worse overall survival (HR, 1.03; 95% CI, 1.00-1.06; p = 0.02), compared to unexposed patients in adjusted models.
Conclusion
Exposure to a wildfire disaster during radiotherapy is associated with worse overall survival among patients with stage III non-operable NSCLC. This finding underscores the critical need for developing adaptation strategies within the healthcare sector, especially in oncology.
Machine learning and data-driven inverse modeling of metabolomics unveil key process of active aging
Authors: Li Jiahang , Brenner Martin , Pierides Iro , Wessner Barbara , Franzke Bernhard , Strasser Eva-Maria , Waldherr Steffen , Wagner Karl-Heinz , Weckwerth Wolfram 
Published: November 2024

Abstract

Physical inactivity and weak fitness status have become a global health concern. Metabolomics, as an integrative systematic approach, might link to individual’s fitness at the molecular level. In this study, we performed blood samples metabolomics analysis of a cohort of elderly people with different treatments. By defining two groups of fitness and corresponding metabolites profiles, we tested several machine learning classifications to identify key metabolite biomarkers, which showed robustly aspartate as a dominant negative marker of fitness. Following, the metabolomics data of the two groups were analyzed by a novel approach for metabolic network interaction termed COVRECON. Where we identified the enzyme AST as the most important metabolic regulation between the fit and the less fit groups. Routine blood tests in two cohorts validated significant differences in AST and ALT. In summary, we combine machine-learning classification and COVRECON to identify metabolomics biomarkers and causal processes for fitness of elderly people.
Preparation of CeZrO2 with mixed alcohol/water solvents: as highly active catalysts for the synthesis of dimethyl carbonate from CO2 and methanol
Authors: Wang Yaning , Qi Guisheng , Guo Yujing , Li Ning , He Jingting , Guo Qiang , Liu Youzhi 
Published: November 2024

Abstract

Synthesis of dimethyl carbonate (DMC) from carbon dioxide (CO2) is a representative pathway for CO2 resource utilisation, which can effectively reduce atmospheric CO2 levels. CeZrO2 can effectively catalyse the generation of dimethyl carbonate (DMC) by direct reaction of carbon dioxide (CO₂) and methanol (MeOH). However, its morphologically controllable synthesis and resolution of particle agglomeration remain a challenge. In this paper, uniformly dispersed rod-like structures were synthesised by adjusting the composition of the reaction solvent during CeZrO2 synthesis. Experiments and characterisation showed that the addition of alcohol directly affected the morphology and aggregation of ions in solution and promoted the reduction of Ce4+ to Ce3+, thus improving the catalytic performance of rod-shaped CeZrO2. When n-butanol was added at an alcohol-to-water ratio of 1/1, the generation of DMC has been optimised at 4.36 mmol/g, which was about 10% higher than the performance of DMC from a single aqueous solution. In this work, a simple, efficient and rapid modification method was used to achieve the improvement of catalyst performance, and the modulation of the reaction solvent can effectively reduce the cost of catalyst production compared with the doping modification of the catalyst with metal elements, and this study is an important reference for the optimisation of the performance of other types of catalysts.
A restaurant recommendation method that combines neural network algorithms and information extraction from electronic word of mouth
Authors: Gregoriades Andreas , Herodotou Herodotos , Pampaka Maria , Christodoulou Evripides 
Published: November 2024

Abstract

Recommendation systems are popular information systems that help consumers manage the information overload problem, encountered when making decisions with many alternatives. One type of such systems are restaurant recommenders. Whilst personality has been recognized as important for influencing consumers’ choice, it has not yet been exploited in restaurant recommendation with dominant recommendation technique in this sector being collaborative filtering. This work proposes a restaurant recommendation method that exploits personalities, opinions and preferences of customers that are either extracted directly from online review platforms or derived from text in electronic word of mouth (eWOM), using information extraction techniques. The proposed method introduces the concept of venue personality based on theory stipulating that customers are more satisfied with brands that have similar personality to their own. A novel deep learning model is designed to extract personality from text and is used to assess customers and venues’ personalities. Food preferences are extracted from eWOM via a custom named-entity recognizer. Customer opinions are extracted from eWOM’s text through topic modelling. Latent information regarding customer preference are extracted form the interactions of customers with restaurants via a neural collaborative filtering (NCF) component. The embeddings of the NCF component are extracted and combined with the above features to form the input based on which an extreme gradient boosting (XGBoost) model is trained to predict restaurants ratings. Results are compared to baseline models using various performance metrics and verify that the method improve restaurant recommendation.
Antibiotic type and dose variably affect microbiomes of a disease-resistant Acropora cervicornis genotype
Authors: Patton Sunni , Silva Denise , Fuques Eddie , Klinges Grace , Muller Erinn , Thurber Rebecca Vega 
Published: November 2024

Abstract

Background
As coral diseases become more prevalent and frequent, the need for new intervention strategies also increases to counteract the rapid spread of disease. Recent advances in coral disease mitigation have resulted in increased use of antibiotics on reefs, as their application may halt disease lesion progression. Although efficacious, consequences of deliberate microbiome manipulation resulting from antibiotic administration are less well-understood – especially in non-diseased corals that appear visually healthy. Therefore, to understand how healthy corals are affected by antibiotics, we investigated how three individual antibiotics, and a mixture of the three, impact the microbiome structure and diversity of a disease-resistant Caribbean staghorn coral (Acropora cervicornis) genotype. Over a 96-hour, aquarium-based antibiotic exposure experiment, we collected and processed coral tissue and water samples for 16S rRNA gene analysis.
Results
We found that antibiotic type and dose distinctively impact microbiome alpha diversity, beta diversity, and community composition. In experimental controls, microbiome composition was dominated by an unclassified bacterial taxon from the order Campylobacterales, while each antibiotic treatment significantly reduced the relative abundance of this taxon. Those taxa that persisted following antibiotic treatment largely differed by antibiotic type and dose, thereby indicating that antibiotic treatment may result in varying potential for opportunist establishment.
Conclusion
Together, these data suggest that antibiotics induce microbiome dysbiosis – hallmarked by the loss of a dominant bacterium and the increase in taxa associated with coral stress responses. Understanding the off-target consequences of antibiotic administration is critical not only for informed, long-term coral restoration practices, but also for highlighting the importance of responsible antibiotic dissemination into natural environments.