bluuebunny/crossref_metadata_2025_split huggingface dataset:
Is The Serum Creatinine / Alanine Transaminase Ratio A Predictor Of Mortality In Elderly Patients With Acute Ischemic Stroke?
Authors: Yılmaz Özgür , Yılmaz Ayşe , Soylu Veysel Garani , Taşkın Öztürk , Demir Ufuk , Kurada Gizem , Tanyıldızı Büşra , Doğanay Zahide 
Published: July 2024

Abstract

Background
This study by aiming to investigate the relationship of serum creatinine/alanine transaminase ratio(sCr/Alt) with mortality of patients aged 85 and over treated for acute ischemic stroke
Methods
Medical records of patients aged 85 and over treated for acute ischemic stroke between January-2017 and October-2021 were evaluated. A total of 189 patients over the age of 85 with a diagnosis of cerebrovascular disease were included in the study.
Results
When we evaluated the 28-day mortality prediction performance of the variables, ALT(p < 0.001), serum creatinine(p < 0.001), serum creatinine/alanine transaminase(p < 0.001) were significantly higher in the mortal cases than in the other patients. We evaluated the 28-day mortality prediction performances of the variables, the sCr/Alt ratio was found to have 85.4% sensitivity and 84.8% specificity.
Conclusion
sCr/Alt value is a more valuable marker compared to NIHSS, APACHE II and SAPS II values which are mortality markers in advanced elderly patients with acute ischemic stroke in intensive care.
Hidden Dynamics of a Self-excited SD Oscillator
Authors: Bandi Dinesh , TAMADAPU GANESH 
Published: July 2024

Abstract

The present study explores the nonlinear dynamics of a self-excited smooth and discontinuous (SD) oscillator with geometric nonlinearity at the switching surface. Using a novel framework called hidden dynamics, introduced by Jeffrey, the research addresses the challenge posed by dry friction oscillators where the static friction coefficient is greater than the kinetic friction coefficient, which is ignored in Filippov’s theory. By modelling the belt friction in the SD oscillator as Coulomb friction, we investigate the consequences of the discontinuity in the friction model. The sliding regions were determined analytically and validated through numerical simulations. The system's behaviour is analyzed through the examination of bifurcation diagrams and phase portraits, and a comparison is conducted with Filippov’s theory. Some interesting bifurcation phenomena are highlighted, including a novel phenomenon involving the collision and merging of two degenerate boundaries and the bifurcation of a sliding homoclinic orbit to a saddle. Furthermore, the system's response to harmonic excitation is analyzed, wherein the oscillator displays stick-slip limit cycles, pure slip limit cycles and the emergence of chaotic solutions through periodic doubling bifurcation.
The influence of body posture on facial expression perception in Autism
Authors: Finn Abigail , Shah Punit , Rosa Stephan de la , Teufel Christoph , Hagen Elisabeth von dem 
Published: July 2024

Abstract

Facial expression perception is influenced by body posture, with perception biased toward the body emotion. Previous research has suggested that the magnitude of this biasing influence of body posture is driven by individual differences in the precision of facial expression representations underlying discrimination abilities, where lower precision leads to a greater influence of body posture. It is unclear however whether similar mechanisms might drive the influence of contextual cues in Autism, which is often characterised by reduced facial expression discrimination abilities. Here, we addressed this question by using online psychophysical methods to determine the precision of isolated face and body expression representations, as well as the influence of body posture on facial expression perception, in autistic and non-autistic adults. Both groups showed a strong influence of body context on facial expression perception, but this influence was larger in the autistic group, mirroring their lower overall precision of facial expression representations relative to non-autistic individuals. Crucially, the magnitude of the biasing influence of body posture in both groups was related to the precision of individuals’ facial expression representations. The results suggest that similar principles govern the integration of facial expression and body posture information in both autistic and non-autistic individuals.
Apparent Diffusion Coefficient as a Prognostic Indicator in Definitive Radiotherapy for Gleason Score 7 Prostate Cancer: A Retrospective Analysis
Authors: Onal Cem , Elmali Aysenur , Erbay Gurcan , Demirhan Birhan , Guler Ozan Cem 
Published: July 2024

Abstract

Objective
To investigate the utility of diffusion-weighted magnetic resonance imaging (DW-MRI) in evaluating Gleason score (GS) 7 tumors before definitive radiotherapy (RT) and to explore its association with clinicopathological factors and treatment outcomes.
Methods
Clinical data of 266 prostate cancer (PCa) patients with biopsy-confirmed GS 7 who underwent RT were retrospectively analyzed. Pre-treatment DW-MRI was utilized to measure apparent diffusion coefficient (ADC) values of primary tumors. Treatment outcomes, including biochemical disease-free survival (bDFS) and prostate cancer-specific survival (PCSS), were assessed. Statistical analyses were conducted to determine the correlation between tumor ADC values, clinicopathological factors, and treatment outcomes.
Results
Tumors with a GS of 3 + 4 had significantly higher ADC values than those with a GS of 4 + 3 (0.746 ± 0.150 vs. 0.702 ± 0.157 × 10˗³ mm²/sec; p < 0.001). Median follow-up time was 8.6 years, and the 7-year rates for bDFS and PCSS were 89.1% and 95.3%, respectively. Lower tumor ADC values were significantly correlated with higher GS and increased risk of disease progression. A primary tumor ADC cutoff value of 0.682 × 10˗³ mm²/sec was identified for predicting disease progression. Patients with higher ADC values exhibited significantly better 7-year bDFS rates (92.8% vs. 83.2%; p = 0.02). However, GS 4 + 3 tumors independently predicted poorer bDFS and PCSS outcomes. In the multivariable analysis, only GS 4 + 3 tumor was predictive for worse bDFS and PCSS.
Conclusions
Tumor ADC values are a reliable biomarker for differentiating between GS 3 + 4 and 4 + 3 tumors in the GS 7 category. Tumors exhibiting lower ADC values have been associated to higher risk factors and an increased likelihood of disease progression, particularly in GS 3 + 4 tumors where GS upgrading could happen.
Assessing the stability and adaptability of corn hybrid yield with the Bayesian AMMI model
Authors: Silva Eliam Vitor Pereira da , Davide Livia Maria Chamma , Gianlup Camila , de Oliveira Wanderley Jorge Soares , de Oliveira Luciano Antonio , Silva Alessandra Querino da , Silva Carlos Pereira da , Mendes Cristian Tiago Erazo , Khan Shahid 
Published: July 2024

Abstract

The objective of this work was to evaluate the stability and adaptability of commercial and experimental corn hybrids tested in three locations in Mato Grosso do Sul (MS) in the 2021 and 2022 agricultural years. We identified superior genotypes that can be recommended broadly and/or restrictedly to optimize productivity. The randomized complete block design (RCBD) was used to evaluate the grain yield per plot (ton/ha) with the additive main effects model and multiplicative interaction via Bayesian inference (BAMMI). It was observed from the results that the genotype by environment interaction (G x E) did not behave in a complex way and that the genotypes, in general, do not have significant contributions to the interaction. Furthermore, it was found that stable and productive hybrids can be selected regardless of genetic structure. The G26 genotype, which is the simple commercial hybrid B2702, stood out as one of the best cultivars. However, it was observed that there are experimental hybrids as good as B2702, such as G9, which is a double hybrid. This result is relevant since double hybrid cultivation is more viable in low investment contexts, as occurs in family farming. Finally, the BAMMI model proved to be a versatile tool with flexibility to overcome the limitations inherent to classical and frequentist analyses of linear-bilinear models.
Knowledge Representation Learning Based on Neighborhood Semantics
Authors: Fu Zijian , Li Dun 
Published: July 2024

Abstract

Knowledge representation is a key technology for knowledge acquisition, application and construction of knowledge graphs. Aiming at the problem of insufficient information utilization in current knowledge representation learning models, a knowledge representation learning model based on neighborhood semantics is proposed. This model focuses on generating hybrid neighborhood representations that blend entity neighborhood details. In addition, it combines entity semantic category information with mixed neighborhood as a unit to extend the entity's semantic category to neighborhood semantic categories. Comparative experiments show that our model outperforms other models in terms of metrics, such as MR, HITS@K in the link prediction, and Micro-ACC and Macro-ACC for triplet classification.
A study on the molecular mechanism of Baicalin in improving Myocardial Fibrosis based on network pharmacology and experimental verification
Authors: Zhang Minghao , Wu Liujun , Shen Yanduo , Zhang Jiale , Xie Bingheng , Wu Xingfei , Wei Danan 
Published: July 2024

Abstract

This study aimed to evaluate the pharmacological mechanism of baicalin intervention on myocardial fibrosis through network pharmacological analysis, molecular docking, and experimental verification.The chemical components and targets of all the drugs in the Baicalin were obtained through Target Prediction databases. The targets of Myocardial fibrosis(MF)were screened through the GeneCards and OMIM databases. The obtained targets were imported into Cytoscape 3.9 software to construct the active ingredient target network and were imported into the String database to construct PPI network, and the in Cytoscape 3.9 was used for network topology analysis. Gene Ontology (GO) enrichment analysis and Kyoto gene and genomic (KEGG) enrichment analysis were performed on the potential targets of Wuling decoction for MF using the David database.The results were imported into bioinformatics platform to obtain GO and KEGG network relationship maps. The molecular docking software AutoDock Vina was used to dock the core targets with the active ingredients. A MF rat model was established and animals were divided into the control, MF model, a captopril group (9 mg/kg), and low-, middle-, and high-dose baicalin groups (50, 100, 200 mg/kg). Compared with the rats in the MF model group, rats in each administration group demonstrated restoration of ST segment amplitude and T wave on electrocardiograms. Moreover, HWI and LVWI exhibited significant decreases. The levels of CK, LDH, NT-proBNP, Col I and Col III in myocardial tissue also showed significant decreases. Additionally,the degree of myocardial fibrosis was reduced; there were also significant decreases observed in the expression levels of PTGS2 and TNF-α in myocardial tissue, where as an increase was noted in the expression level of IL2. Baicalin has been shown to enhance myocardial fibrosis and cardiac function in a rat model of myocardial fibrosis. The mechanism underlying this effect appears to be associated with the down-regulation of PTGS2 and TNF-αexpression levels, as well as the up-regulation of IL2 expression levels.
Bioinformatics analysis and Late Blight resistance identification of zinc finger protein gene StZFP16
Authors: He Miaomiao , Zhu Di , Zhou Yun , Yang Shenglong , Sun Haihong , Wang Jian 
Published: July 2024

Abstract

Late blight is the most notorious oomycete disease in potato production. Qingshu 9 has been the leading potato cultivar Qingshu 9 in China, which showed excellent field performance against late blight in different regions and multiple years. Based on the transcriptome data of the interaction between Qingshu9 and late blight in the early stage of the research group, zinc finger protein genes plays a critical role in interaction between late blight and Qingshu9. In this study, a novel gene, StZFP16 was cloned from Qingshu 9. The total length of StZFP16 is 1107 bp, and it encodes 369 amino acid polypeptides. The StZFP16 was induced by SA and MeJA to express. An overexpression vector of StZFP16 was constructed and transiently transformed into the model plant Nicotiana benthamiana. And the results showed that StZFP16 gene enhances plant resistance to late blight by mediating H2O2 content, antioxidant enzyme activity and the expression of related defense genes. These results indicated that StZFP16 enhanced potato resistance to P. infestans, providing a vital theoretical basis for analyzing the functional diversity of zinc finger protein family genes and the effective utilization of Qingshu 9 in disease resistance breeding.
Towards LLMCI - Multimodal AI for LLM-Vision UI Operation
Authors: Barham Husam , Fasha Mohammed 
Published: July 2024

Abstract

Human-computer interaction (HCI) has evolved significantly, yet it still largely depends on visual communication through screens and manual input devices. While this paradigm is likely to remain dominant for the foreseeable future, this research suggests that existing user interfaces (UI) can also be leveraged by Large Language Models (LLMs) to interact with computers. By integrating vision models into a multimodal framework, LLMs can gain the ability to understand and operate UI elements, enabling them to retrieve information, run functions, and perform various tasks just like humans. The framework utilizes a vision model to communicate UI components and information to the LLM, which then leverages its language understanding capabilities to retrieve information, and operate keyboard and mouse inputs.This paper introduces a new element to Human-Computer Interaction (HCI), called LLM-Computer Interaction (LLMCI), which combines Large Language Models (LLMs) with computer vision via intelligent agents. These agents process user text commands and use visual perception to recognize visual and textual elements of computer interfaces. This allows the Multimodal AI to independently perform complex tasks and navigate applications in a way that resembles human behavior. We present a proof-of-concept framework that illustrates how the agent uses LLMs and computer vision to handle interface elements, complete tasks, and support users according to their instructions. This strategy closely imitates human interactions and suggests a path forward for enhancing HCI practices.
Heart rate variability biofeedback intervention programme to improve attention in primary schools
Authors: Ruiz Ainara Aranberri , Seco Malen Migueles 
Published: July 2024

Abstract

The importance of attentional capacity for academic performance is highlighted by the increasing demands placed on students during primary school. Between the ages of 6 and 12, there is an evolutionary improvement in attentional capacity and the school environment is shown to be an appropriate setting in which to develop programmes to improve attention. Heart rate variability is an appropriate indicator of attentional capacity. For all these reasons, a heart rate variability biofeedback intervention focused on breathing was developed and implemented to improve attention. The intervention consists of two phases. In the first phase, the teachers of the school are trained to develop the intervention. In the second phase, the students receive 5 individual sessions from their teachers. In each individual session, they learn to breathe in a way that increases their heart rate variability. A total of 272 girls and 314 boys (N=586) aged 6-12 years participated in the programme. In order to study the impact on the three cycles of primary school, the attention of the control and experimental groups was assessed before and after the implementation of the programme. According to the data obtained, despite developmental improvements, the students who participated in the programme showed an increase in heart rate variability and an improvement in attentional capacity, with a greater impact on the first cycle of primary school. Our conclusion is to discuss the usefulness of heart rate variability biofeedback interventions in improving attention in primary school children and to present arguments for their use.
WITHDRAWN: Development of a Novel Hybrid Salp Swarm-Kepler Algorithm for Engineering Problems: Optimizing Microgrid Sizing with Integration of Photovoltaic, Wind, Battery, and Supercapacitor Systems
Authors: Güven Aykut Fatih 
Published: July 2024

Abstract

Economic growth accelerates, leading to an increasingly important need for efficient resource use in engineering design due to the resulting supply and demand imbalance. This study introduces an integrated hybrid application of the Salp Swarm Algorithm (SSA) and the Kepler Optimization Algorithm (KOA) to optimize engineering design problems. The integration of SSA’s mathematical modeling of salp movement and leader-follower dynamics, along with KOA's optimization mechanisms based on Kepler’s laws, provides significant advancements in avoiding local optimum traps and achieving balance in the search space. The hybrid SSAKOA algorithm is capable of quickly reaching optimal or near-optimal solutions to optimization problems while efficiently working across parameters. Experimental results show that SSAKOA outperforms other algorithms in terms of optimum performance, solution stability, and applicability, effectively reducing resource wastage in engineering designs. The optimization capability of the SSAKOA has been verified for 23 different function problems, revealing that SSAKOA offers higher convergence speed, precision, and robustness than other algorithms. Moreover, this algorithm has yielded the most optimal results compared to 12 different algorithms in sizing a microgrid consisting of grid-connected batteries, supercapacitors, wind turbines, and photovoltaic panel components, which poses a significant engineering challenge. This study demonstrates the effectiveness of the proposed algorithm by applying it to a hybrid renewable energy system on a Turkish university campus. The application reveals an annual cost of $572,369.93 and an energy cost of $0.23996/kWh, achieving a renewable energy fraction of 78.54%. This indicates that the system not only offers a cost-effective alternative to Turkey's conventional grid rate of $0.35/kWh but also underscores the algorithm’s potential in enhancing the economic and environmental sustainability of renewable energy projects. Such findings lay a foundational framework for future advancements in renewable energy applications.
Enhancing PLA Filament Biocompatibility by introducing ZnO and Ketoprofen
Authors: Neto Thalita Silva , Maia Lana S. , Conceição Monique O. T. , Silva Maryana B. , Carvalho Layde T , Medeiros Simone F. , Faria Maria Ismênia S. D. , Migliorini Bianca B. , Lima Renata , Rosa Derval S. , Mulinari Daniella R. 
Published: July 2024

Abstract

This study investigates the incorporation of zinc oxide (ZnO) and ketoprofen (keto) into poly(lactic acid) (PLA) filaments to enhance their biocompatible. PLA is widely used in additive manufacturing, especially in biomedical applications, due to its biodegradability and biocompatibility. However, its interaction with biological tissues can be improved. ZnO was chosen for its wound-healing properties, while keto, a nonsteroidal anti-inflammatory drug, was selected to provide local anti-inflammatory effects. PLA filaments were prepared by incorporating ZnO and keto, followed by analyses of their mechanical, thermal, and biological properties. The results showed that the incorporation of ZnO and keto did not compromise the mechanical and thermal properties of the PLA filaments. Compared to pristine PLA, the composites presented a slight improvement in strength. The incorporation of ketoprofen in the composite increased its thermal stability compared to PLA-ZnO filament. Concerning the morphology, when ZnO and Keto were inserted, the scaffold acquired a more robust structure, with well-defined porosity. In vitro biocompatibility tests indicated that the modified filaments exhibited lower cellular toxicity and improved cell adhesion and proliferation compared to pure PLA. Antimicrobial tests demonstrated that the filaments containing ZnO, at the evaluated concentration, did not exhibit activity against Staphylococcus aureus, Escherichia coli and Pseudomonas aeruginosa, gram-positive and gram-negative bacteria. The combination of ZnO and ketoprofen in PLA filaments can enhance their biomedical applications, providing better biocompatibility without compromising the intrinsic characteristics of PLA. This work paves the way for the development of safer and more effective medical implants and devices.
Genome interrogation of homeostatic calcium activity using CaMP-screen
Authors: Carreras-sureda Amado , Kouba Sana , Zhang Xin , Castelbou Cyril , Demaurex Nicolas 
Published: July 2024

Abstract

Calcium signals regulate crucial cellular functions yet many genes coding for Ca2+ handling proteins remain unknown as their identification relies on low-throughput single-cell approaches. Here we describe a novel method to measure Ca2+ activity in cells isolated by flow cytometry following pooled genome interrogation. Using a CRISPR/ CAMPARI2 screen, we identified enhancers and inhibitors of homeostatic Ca2+ activity.
Dog ectoparasites as sentinels for pathogenic Rickettsia and Bartonella in rural Guatemala
Authors: Tian Yuexun , Juarez Jose G. , Moller-Vasquez Andrea M. , Granados-Presa María , Ferreira Francisco C. , Pennington Pamela M. , Padilla Norma , Hamer Gabriel L. , Hamer Sarah A. 
Published: July 2024

Abstract

Background: Fleas and ticks serve as vectors of multiple pathogens in the genera Rickettsia and Bartonellathat cause diseases in humans and other animals. Although human rickettsiosis and bartonellosis have been reported in all countries in Central America, limited research has been conducted to investigate the natural cycles of flea- and tick-borne rickettsiosis and bartonellosis, especially in Guatemala.
Methods: We evaluated dog parasites as sentinels for zoonotic disease risk in rural Guatemala by sampling ticks and fleas from dogs, which were then identified and individually screened for Rickettsia and Bartonella.
Results: A total of 77 households were surveyed and 80.52% of them had dogs. Overall, 133 dogs were examined for fleas and ticks, of which 68.42% had fleas and 35.34% had ticks. A total of 433 fleas and 181 ticks were collected from the infested dogs, with an additional 33 ticks collected from house walls. Three flea species were identified: Ctenocephalides felis (70%), Echidnophaga gallinacea(11.8%), and Pulex sp. (17.8%). Among the collected ticks, 97% were Rhipicephalus sanguineus with the rest being Amyblyomma cajennense, A. auricularium, and A. ovale. Rickettsia felis were detected in six C. felis, in one Pulex sp., and in two R. sanguineus, while Candidatus R. senegalensis was detected in one C. felis. Bartonella was detected only in fleas, including three Pulexsp. infected with B. vinsonii subsp. Berkhoffii, B. henselae, and Bartonella sp., respectively, and 11 C. felis infected with B. henselae.
Conclusions: This study reports Candidatus R. senegalensis and B. vinsonii subsp. Berkhoffiiin Guatemala for the first time, and indicates the potential risk of human and dog exposure to Rickettsia and Bartonella species. These results show that dogs provide critical information relevant to managing human potential exposure to flea- and tick-borne pathogens in rural Guatemala.