bluuebunny/crossref_metadata_2025_split huggingface dataset:
A nomogram of the clinical factors associated with lymph node metastasis of early gastric adenocarcinoma before surgery
Authors: Yan Zhang , Gang Liu , Zhen Cao , Zhanwei Zhao , Tong Han , Yun Huang , Guandi Ding 
Published: October 2024

Abstract

Gastric cancer is a relatively occult digestive tract tumour whose incidence and mortality are among the top five in the world. The latest cancer statistics in China show that the incidence and mortality of gastric cancer are on the rise. Recent research has shown that the lymph node metastasis of tumour cells from lymphatic vessels into the systemic circulation is likely to lead to metastasis, and it is the main source of tumour cells for distant metastasis. Lymph node metastasis usually seriously shortens the survival time of cancer patients. For patients with early gastric adenocarcinoma, early prediction and intervention of those who may have lymph node metastasis after surgery through appropriate observation indicators is expected to greatly reduce their mortality, prolong their survival and achieve better therapeutic effects. In this study, we comprehensively evaluated the biological behaviour of early gastric adenocarcinoma with lymph node metastasis after surgery, analysed the associations of routine laboratory indices and histopathological diagnosis with lymph node metastasis, and used the ascending segment of a nomogram to identify the high-risk group for preoperative lymph node metastasis. This case‒control study enrolled 600 patients, including 354 patients with lymph node metastasis and 246 patients without lymph node metastasis in North China. The least absolute shrinkage and selection operator (LASSO) regression model and multivariate logistic regression were used to analyse the risk factors for patients with lymph node metastasis of early gastric adenocarcinoma before surgery. Four variables (diabetes mellitus, pathological stage, tumour size, and CEA level) were input into a nomogram model of disease progression. The C-index, ROC curve, DCA and calibration curve showed that the model had good discrimination and accuracy in the development group and the validation group. The clinical impact diagram showed that the nomogram for patients with preoperative lymph node metastasis of early gastric adenocarcinoma has high clinical application value.
A new approach to experimental charcoal analyses: lessons for the Cretaceous and other time periods
Authors: Galinger Matthew , Vachula Richard , Goertzen Leslie , Hansen Curtis , Cullen Thomas 
Published: October 2024

Abstract

Earth’s climate has historically oscillated between climate states, with greenhouse climate periods offering valuable analogs for future climate projections. The Cretaceous period, characterized by high atmospheric CO2 levels and the absence of polar ice caps, provides insights into potential ecological responses to anthropogenic climate change. This study presents experimental data to inform the use of sedimentary charcoal as a paleofire and palaeoecological proxy during the Cretaceous, supplementing the limitations of traditional palynological and fossil perspectives. Our experimental analysis includes 23 broadly sampled plant taxa, focusing on charcoal morphological classifications and a novel set of the following morphometric parameters: aspect ratio (L:W), rectangularity, circularity, and feret diameter. Our results reveal significant differences in charcoal morphometrics at the tissue (e.g., leaf, petiole) and component (e.g., vein, blade) levels, challenging the assumption that larger plant tissues produce relatively uniform charcoal particles. This emphasizes the need for refined morphometric techniques that consider plant tissues as an assemblage of their respective components. Our findings provide a nuanced framework that will improve the accuracy of future charcoal-based paleofire and paleoecology studies, particularly in pre-Holocene contexts, aiding predictions of future ecological dynamics under changing climate conditions.
Microwave-assisted multicomponent synthesis of spiro[indoline-3,4'-pyrazolo[3,4-b]quinoline]-2,5'(6'H)-diones catalyzed by Ionic liquid-coated magnetic carbon nanotubes
Authors: Altalbawy Farag M. A. , Khelif Ali , Saraswat Shelesh krishna , Makasana Jayanti , Jyothi Renuka , Bhanot Deepak , Kumari Bharti 
Published: October 2024

Abstract

We synthesized CNTs-Fe3O4-IL, which are multi-walled carbon nanotubes modified with an imidazolium-ionic liquid. Then, we conducted a comprehensive analysis of the structure, morphology, and properties of the nanocomposites using various characterization techniques. These techniques included VSM, FT-IR, TEM, TGA, DTA, SEM, and XRD. In this manuscript, a novel and efficient microwave-assisted multicomponent synthesis method for spiroindoline-3,4'-pyrazolo[3,4-b]quinoline-2,5'(6'H)-diones using ionic liquid-coated magnetic carbon nanotubes as the catalyst is presented. The synthesis involves the condensation of 3-methyl-1H-pyrazole-5-amins, cyclohexane-1,3-diones, and isatin derivatives under microwave irradiation in the presence of ionic liquid-coated magnetic carbon nanotubes. Ionic-liquid-coated magnetic carbon nanotubes serve as a catalyst for this synthesis, providing improved efficiency and separation ability. The catalyst was also tested for reuse and retained almost all of its activity after several cycles, proving that this method is highly sustainable. This study proves that this approach is an effective and environmentally friendly method for obtaining various spirocondensed heterocyclic compounds. This new method will allow the rapid synthesis of biologically active compounds with potential applications in drug discovery and materials science.
Stress management behavior and its associated factors among diabetes patients: A cross-sectional study in the northern Shoa Zone, Ethiopia
Authors: Eshete Akine , Kebebew Gizachew , Asegidew Wondesen , Kifleyohans Tewodros , Deress Tilahun , Assefa Yibeltal 
Published: October 2024

Abstract

Background
Despite evidence supporting the positive impact of effective stress management on diabetes care, self-stress management remains a challenge for diabetic patients worldwide, including in Ethiopia, where research on self-stress management is lacking. This study examines stress management behaviors and their factors among individuals with diabetes.
Method
A facility-based cross-sectional study was conducted in public hospitals of North Shoa Zone from September 1–29, 2023. The study included 422 diabetic patients randomly selected from four public hospitals. Data entry was performed via Epi Data V.3.1, followed by analysis via SPSS version 22. Continuous variables are presented as the means and standard deviations, whereas categorical variables are expressed as percentages. Descriptive statistics were employed to summarize the study variables. To identify factors associated with stress management practices, binary logistic regression models were utilized. A p value of ≤ 0.05 and an odds ratio (OR) with a 95% confidence interval (CI) were considered indicative of statistically significant associations.
Results
Stress management practices were observed in 50.7% of the patients (95% CI: 46.5–55.6%). After adjusting for confounders, factors associated with greater engagement in stress management included formal education (AOR:1.77, 95% CI:1.29–2.77), good diabetic self-care knowledge (AOR:1.90, 95% CI:1.22–2.99), good health promotion services (AOR:2.02, 95% CI: 1.30–3.14), urban residence (AOR: 2.06, 95% CI: 1.29–3.28), and the absence of comorbidities (AOR:2.09, 95% CI:1.33–3.28).
Conclusion
The findings of this study reveal a significant gap in stress management practices, emphasizing the urgent need for healthcare providers in diabetes care to prioritize the implementation of strategies that strengthen patient education, expand self-care knowledge, and deliver holistic health promotion services.
Robust Security Framework for IoT-Enabled Smart Cities: Leveraging Ensemble Machine Learning Techniques in Fog Computing Environments
Authors: Kumari Radhika , Kaur Kiranbir 
Published: October 2024

Abstract

In IoT domains, particularly those reliant on fog computing, possessing enhanced threat detection abilities is crucial. The decentralization and large number of devices, common in smart city environments, make these situations more challenging. Basic security controls are usually inadequate in a complicated and dynamic setting, which calls for innovative approaches to thwarting such intimidation. The gravity of these issues caused the authors to devise a hybrid approach incorporating Gradient Boosting Machines (GBM), Random Forest (RF), and AdaBoost algorithms. The hybrid algorithm combines the advantages of different approaches and minimizes the disadvantages of the individual approaches. The purpose of this research is to conduct an analysis of smart city security literature and assess whether ensemble models are more effective than individual models in the single model approach. The study used two datasets: the University of New South Wales-Network Based 15 (UNSW-NB15) and the Canadian Institute of Cybersecurity Intrusion Detection Systems 2017 (CICIDS2017). The performance metrics of the ensemble model were not only better than that of any single model but also achieved a respectable figure of 95.60% and even 96.67% accuracy on the UNSW-NB15 dataset and CICIDS – 2017, respectively. Key performance metrics showed significant improvements, including precision of 98.78% on UNSW-NB15 and 99.87% on CICIDS2017, recall rates of 99.13% and 99.85%, and F1-scores of 97.32% and 99.64%. These results validate the efficiency of ensemble techniques in safeguarding IoT-based smart city infrastructures, offering enhanced security mechanisms and improved response to evolving cyber threats.
Investigating the causal relationship between Carbon Dioxide Concentrations and Temperature: A Panel Data Approach
Authors: Amendola Marco , Triacca Umberto , Valente Marco 
Published: October 2024

Abstract

The specific details of the relationship between global warming and carbon dioxide concentration have been a long-debated issue in the climate change literature. In this paper we revisit the topic using a panel data approach. In particular, we use the Dumitrescu-Hurlin panel causality test for a panel of individual areas of the planet to assess the causality relation at global level. Moreover, we perform separate individual area-level Granger causality tests to determine the existence and direction of causal links between the two variables at local level. We find evidence of both causality directions at global level, suggesting a potential feedback between CO2 concentration and temperature, and a strong differentiation of the causality links across geographical areas.
Response of soil carbon dioxide emission, soil organic carbon andmicrobial community to biochar addition with nitrogen optimizing
Authors: Yang Weijun , Zhang Liyue , Zhang Jinshan , Li Pengying , Jia Hongtao , Su Lili , Wang Zi 
Published: October 2024

Abstract

A three-year field study was conducted to investigate the CO2 emissions from irrigation wheat fields in response to biochar addition and nitrogen optimizing. Eight treatments were established: (1) control (without any fertilizers or biochar addition, CK), (2) nitrogen fertilizer application alone (300kg/hm2, N1), (3) biochar application alone (20t/hm2, B), (4) nitrogen fertilizer applied with biochar (N1B), (5) nitrogen fertilizer applied with 15% reduction (255kg/hm2, N2), (6) 15% reduction of nitrogen fertilizer + biochar (N2B), (7) nitrogen fertilizer applied with 30% reduction (210kg/hm2, N3), and (8) 30% reduction of nitrogen fertilizer + biochar (N3B), each treatment has three replicates. The objective of this study was to assess the impact of biochar addition and nitrogen optimized levels on soil carbon dioxide emission, soil organic carbon and microbial community. The findings indicated that the application of biochar and/or nitrogen fertilizer, particularly in combination, was observed to increase soil organic carbon and soil active organic carbon. Biochar application decreased CO2 emissions in wheat fields, compared with the non-amendment treatment. Biochar addition combined with optimized nitrogen also make a different CO2 emission rate. This improvement was attributed to the capacity of biochar to regulate soil microbial community composition, like soil functional diversity, soil microorganisms (fungi and bacterial), soil properties (pH, soil bulk density). In conclusion, biochar addition with nitrogen optimizing (B1N2) regime was determined to be the optimal approach for wheat field in irrigated region northern Xinjiang, resulting in enhanced soil organic carbon and the mitigation of carbon emissions. Nevertheless, further investigation of its long-term impact on farmland is recommended.
Isolation and characterization of a novel silicate-solubilizing bacterial strain Staphylococcus ureilyticus MV-1 associated with grape wine
Authors: Nandre Vinod , Mahale Mithil , Patil Rajendra , Kasote Deepak , Sarnikar Sushmita , Kumari Anamika , Kodam Kisan , Kulkarni Mohan , Waghmode Suresh B. 
Published: October 2024

Abstract

This research aimed to isolate Staphylococcus ureilyticus MV-1 bacteria and evaluate their potential for soil application. These bacteria can solubilize silicate minerals up to 25 µg/mL in the first 10 h utilizing magnesium trisilicate as a silica source. This encourages plant development by generating plant hormones such as indole acetic acid (IAA). The IAA production peaked at 14 µg/mL after 48 hours without further supplementation. Further, significant levels of micro- and macro-nutrient uptake were also recorded using Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) in grapevine after treating it with MV-1 indicating the availability of nutrients to plants for proper growth and functioning. The results state that MV-1 had a synergistic effect on plant growth and soil fertility.
In vivo cartography of state-dependent signal flow hierarchy in the human cerebral cortex
Authors: Hong Seok-Jun , Oh Younghyun , Ann Yejin , Lee Jae-Joong , Ito Takuya , Froudist-Walsh Sean , Paquola Casey , Milham Michael , Spreng R. Nathan , Margulies Daniel , Bernhardt Boris , Woo Choong-Wan 
Published: October 2024

Abstract

Understanding the principle of information flow across distributed brain networks is of paramount importance in neuroscience. Here, we introduce a novel neuroimaging framework, leveraging integrated effective connectivity (iEC) and unconstrained signal flow mapping for data-driven discovery of the human cerebral functional hierarchy. Simulation and empirical validation demonstrated the high fidelity of iEC in recovering connectome directionality and its potential relationship with histologically defined feedforward and feedback pathways. Notably, the iEC-derived hierarchy displayed a monotonously increasing level along the axis where the sensorimotor, association, and paralimbic areas are sequentially ordered – a pattern supported by the Structural Model of laminar connectivity. This hierarchy was further demonstrated to flexibly reorganize according to brain states, flattening during an externally oriented condition, evidenced by a reduced slope in the hierarchy, and steepening during an internally focused condition, reflecting heightened engagement of interoceptive regions. Our study highlights the unique role of macroscale directed functional connectivity in uncovering a neurobiologically grounded, state-dependent signal flow hierarchy.
Friction-based Recycling: An Evaluation of Friction Extrusion for Fabricating Ti-6Al-4V Wire Fabricated from Machining Chip Feedstock
Authors: Chouhan Devesh Kumar , Komarasamy Mageshwari , Taysom Scott , Overman Nicole , Canfield Nathan , Roosendaal Timothy , Reynolds Anthony , Whalen Scott 
Published: October 2024

Abstract

Titanium and its alloys are used in aviation and automobile industries due to their remarkable strength to weight ratio, but machining loss commonly is high with ~ 80 wt.% of the material being converted to scrap. Recycling post-consumer Ti scrap directly into solid bulk products is a potential solution for repurposing valuable material. Further, eliminating fresh Ti sponge during recycling might lead to lower energy and greenhouse gas emissions. In this study, a solid-phase process known as friction extrusion was utilized to recycle Ti-6Al-4V machining chips into solid wires which could be used as feedstock in additive manufacturing. The friction consolidation technique was first used to convert chips with varying degrees of oxygen content into solid billets for its use as feedstock material in subsequent friction extrusion. The extrudates were fabricated above the beta transition temperature, which was achieved by selecting the rotation rate and feed rate, to process the billets near 1000°C using a tungsten-lanthana extrusion die. This work presents the first occurrence of friction extruded titanium alloy wires. The effect of friction extrusion on microstructural features, tensile properties, and texture are reported. Overall, the friction extrusion method is capable of directly recycling Ti-6Al-4V scrap into extruded wire.
Comparison of postpartum depression prevalence before and during the covid-19 pandemic in Turkey: a systematic review and meta-analysis
Authors: KARAÇAM Zekiye , EKİN Pirozhan , ŞARALDI Hilal BAL 
Published: October 2024

Abstract

Purpose
To determine the prevalence of postpartum depression and the effect of COVID-19 pandemic on the prevalence of postpartum depression based on the results of the studies in Turkey.
Methods
Systematic review and meta-analysis of cross-sectional studies. The key words postpartum depression or postnatal depression and Turkey were searched in the electronic databases of PubMed, EBSCO, Embase, Web of Science, PsycINFO, Türkiye Atıf Dizini, TR Dizin, DergiPark and YÖK- National Thesis Centre. The systematic review was performed by following PRISMA and COSMOS-E. Data were collected by using a data extraction tool developed by the researchers. The quality of the studies was evaluated by utilizing The Joanna Briggs Institute’s Critical Appraisal Checklist for Analytical Cross Sectional Studies. Obtained data were synthesized with meta-analysis, narrative synthesis, subgroup analysis and meta-regression.
Results
The total sample size of 34 studies included in this meta-analysis was 10 236. The pooled postpartum depression prevalence was 17.8% (95% CI: 0.153–0.206). It was found to be 16.3% before the pandemic (95% CI: 0.065–0.358) and increased to 20.2% during the pandemic (95% CI: 0.068–0.468), though the difference was not significant (Q = 1.77; df: 1; p = 0.184). According to the results of the meta-regression analysis, the geographical region where the study was performed, the postpartum period when data were collected and the cut-off point of the data collection tool used were not effective in the prevalence of postpartum depression. However, there were many factors affecting the postpartum depression prevalence.
Outcomes
This meta-analysis revealed that the postpartum depression prevalence was very high, increased during the pandemic and was affected by many risk factors. It may be recommended that healthcare professionals take protective and improving measures for the mental health of women at high risk during the perinatal period and provide early diagnosis, treatment, monitoring and care services.
The risk of developing acute myeloid leukaemia in patients with Ewing’s sarcoma and trend analysis: A SEER-based study
Authors: Zahed Mohamed , Ellaithy Asmaa , Alesawy Alzahraa Faris , Ali Nahla Ahmed , Zreigh Sofian Mohamed M , Eleisawy Mahmoud , Al-Shaikh Bushra , Hasanin Ekram Hassan , Elsahli Saifaleslam Jamal 
Published: October 2024

Abstract

Background Ewing sarcoma is a neoplasm of neuroectodermal origin arising from bone or soft tissue. The annual incidence of Ewing sarcoma is 2.93 children per 1,000,000. Acute myeloid leukaemia (AML) is one of the most described second malignancies as a complication of primary cancer therapy. There is a lack of recent studies elaborating on the incidence rates of such complications. So, our aim is to quantify the risk of developing AML in Ewing sarcoma patients and provide an updated evidence to the literature.Methods We extracted the data from the surveillance, Epidemiology and End Results (SEER) program statistical analysis software package (SEER*Stat, version 8.4.1.2). We used the MP-SIR session to identify patients diagnosed with acute myeloid leukaemia as a second primary malignancy after Ewing sarcoma as a first primary malignancy between 2000 and 2020. We assessed the SIR as Observed/Expected(O/E) and Excess Absolute Risk (EAR) per 10,000 with a 95% confidence Interval (CI) and statistical significance at P < 0.05.Results A total of 2631 patients with Ewing sarcoma were recorded in the SEER database, with a median follow-up of 120 + months. Patient with Ewing sarcoma had an increased risk to develop AML with O/E of 145.98 (95% CI:101.68 -203.03, P < 0.05, EAR = 21.79). The total cohort of patients had a PC of 32.7, APC of 1.3 (95% [CI] 0.6 -2.0) (P < 0.05). Female patients had a PC of 46.5, APC of 1.7 (95% [CI] 0.5–2.9; P < 0.05). Of relevance, 35 patients developed ANLL with O/E 130.92 (95% [CI] 91.19 -182.08; P < 0.05, EAR 21.77).Conclusion Patients treated for a primary Ewing sarcoma have significant high risk of adeveloping Acute myeloid leukaemia, among other second primary malignancies. We would recommend screening for AML from 2 to 11 months after beginning of Ewing sarcoma treatment.
The potential of bioethanol production in marine yeasts and investigation of the optimal conditions of production in the selected isolates
Authors: Khajeh Banafsheh , Zolgharnein Hossein , Zamani Issac , Ghanemi Kamal 
Published: October 2024

Abstract

Factors such as energy consumption, population growth, and anticipated increases in fuel prices are driving the world towards transitioning to cleaner sources of energy. One promising alternative is the production of bioethanol from marine microorganisms, which is gaining attention due to its economic viability and minimal environmental impact. The objective of this study was to isolate and identify yeast strains from the water and sediments of the Bushehr coast that have the ability to produce bioethanol. Furthermore, the study aimed to determine the optimal production conditions for the most effective strain. 18 yeast strains were isolated and identified using morphological and molecular methods. The results of the molecular analyses showed that the isolated yeasts belonged to the genera Pichia and Candida. After assessing the amount of CO2 produced during the fermentation process, the following strains were selected as the top bioethanol producers: Pichia sp. isolate BK10, Pichia kudriavzevii isolate BK40, Pichia kudriavzevii isolate BK50, Pichia fermentans isolate MK20, and Candida parapsilosis isolate BK30. In our study, we produced bioethanol using the microfermentation method and experimented with different carbon sources like glucose, fructose, lactose, and sucrose. We found that the highest alcohol yield of 12.73% was achieved when glucose was used as the carbon source. Additionally, when we induced mutations with UV-30W light in the superior strain, bioethanol production increased to 15.2%. These marine yeasts have great potential for industrial use in the future, and they could potentially cover alcohol production at the level of small bioreactors.