bluuebunny/crossref_metadata_2025_split huggingface dataset:
Late presentation of chronic myeloid leukaemia patients in a low-income country: The prognostic implications and impact on treatment outcome
Authors: Nelson Elisha Akpowowo , Ahmed Ibrahim Oluwaseun , Bolarinwa Rahman Ayodele , Adeagbo Babatunde Ayodeji , Adegbola Adebanjo Jonathan , Salawu Lateef , Bolaji Oluseye O , Durosinmi Muheez Alani 
Published: June 2024

Abstract

Background
In Nigeria, since 2002, Imatinib mesylate (glivec®) has been available freely to chronic myeloid leukaemia (CML) patients but only at a tertiary health care centre in the south western part of the country. Despite this, it is not readily accessible to many patients due to the distance and other challenges including low socioeconomic status and political problems, thereby preventing timely access specialist care. This study evaluated the effect of the baseline characteristics on the prognostic implication and treatment outcome of CML patients in Nigeria.
Method
This study retrospectively evaluated the medical records of 889 CML patients over an 18 years period (2002–2020). Of these, 576 (65%) patients had complete information with up-to-date BCR::ABL1 record. These 576 patients were categorized based on their responses to Imatinib therapy into three groups viz; Optimal response (OR) defined as BCR::ABL1 ratio of < 0.1% or major molecular remission, Suboptimal response (SR) with BCR::ABL ratio of 0.1–1%, and Treatment failure (TF) when MMR has not been achieved at 12 months. The variables were analyzed using descriptive and inferential statistics and a p-value < 0.05 was considered statistically significant.
Results
The result revealed a median age of 37 years at diagnosis with a male to female ratio of 1.5:1. The majority (96.8%) of the patients presented with one or more symptoms at diagnosis with a mean duration of symptom of 12 ± 10.6 months. The mean Sokal score was 1.3 ± 0.8, with almost half (49%) presenting with a high score. There was a statistically significant positive correlation between Sokal score and duration of symptoms at presentation (r = 0.733, p = 0.011). Based on response categorization, 40.3% had OR while 27.1% and 32.6% had SR and TF respectively.
Conclusion
Low optimal response of 40.3% and treatment failure of 32.6% in CML patients while on first line Imatinib (Glivec®) therapy in our cohort is strongly attributable to long duration of symptoms (> 12months) and high-risk disease (high Sokal score) at presentation. We advocate prompt access to specialist care and de-centralization of the free Imatinib program in Nigeria.
Features of mangrove ecosystems after ten years of restoration on Flores Island, Indonesia
Authors: Wirabuana Pandu , Baskorowati Liliana , Pamungkas Bayu , Mulyana Budi , South Josie , Purnobasuki Hery , Andriyono Sapto , Hasan Veryl 
Published: June 2024

Abstract

Indonesia has extensively reforested mangroves to stabilize coastal ecosystems and mitigate climate change. Reforestation's long-term effects on recovering mangroves are not extensively established because most projects are only observed for two years. It raises the question of whether mangrove replanting aids biodiversity conservation and ecological recovery. This project will characterize Flores Island mangrove ecosystems after ten years of regeneration. The ecological survey took place at Bangkoor, Kolisia, and Talibura reforestation areas. Floristic composition, wildlife diversity, carbon sequestration, and energy storage were measured at each location. Field observations revealed 10 plant and 11 animal species, with flora and fauna species varying by site. Flora diversity was highest in Kolisia and fauna diversity was highest in Talibura. Talibura and Kolisia have similar vegetation and wildlife than Bangkoor. Restored mangrove stands sequestered 28.69 − 70.02 Mg CO2 ha− 1 and stored 30.54×104 − 54.07×104 MJ ha− 1 of energy. Rhizophora apiculata (47.37 ± 5.68 kg CO2) had the most carbon sequestration, while Bruguiera gymnorhiza (645.22 ± 21.65 MJ) had the highest energy storage. Reforestation-induced mangrove ecosystems have biodiversity, carbon storage, and energy stock features.
DNA Methylation Biomarker Panels for the Differentiation of Hepatocellular Carcinoma and Cholangiocarcinoma from Liver Metastases from Colorectal Carcinoma and Pancreatic Adenocarcinoma
Authors: Draškovič Tina , Ranković Branislava , Zidar Nina , Hauptman Nina 
Published: June 2024

Abstract

Background
DNA methylation biomarkers are one of the most promising tools for the diagnosis and differentiation of adenocarcinomas of the liver, which are among the most common malignancies worldwide. Their differentiation is important because of the different prognosis and treatment options. This study validates novel diagnostic DNA methylation panels that focus on DNA hypermethylation in cancer and successfully differentiate between the two most common primary liver cancers (hepatocellular carcinoma and cholangiocarcinoma), two common metastatic liver cancers (from colorectal and pancreatic ductal adenocarcinomas) and healthy liver tissue. Moreover, this study investigates whether hypermethylation of selected DNA methylation biomarkers of primary colorectal carcinoma and pancreatic ductal adenocarcinoma are preserved in their liver metastases.
Methods
Our study included a cohort of 149 formalin-fixed, paraffin-embedded tissue samples. The methylation status of the samples was experimentally determined by methylation-sensitive high-resolution melting and methylation-specific digital PCR. The digital PCR results were additionally validated by bioinformatic analysis using an independent dataset of 487 samples from the TCGA and GEO databases. The sensitivities, specificities and diagnostic accuracies of the panels for individual cancer types were calculated.
Results
The methylation-sensitive high-resolution melting analysis led to the selection of the best biomarker candidates and enabled the development of panels that exhibit a sensitivity of 60–93% and a specificity of 85–98% for all included primary tumors and paired normal tissues. The panels tested with digital PCR show a sensitivity of 66.7–100%, a specificity of 94.9–100% and a diagnostic accuracy of 93–100% for hepatocellular carcinoma, cholangiocarcinoma, healthy liver tissue, colorectal liver metastases and liver metastases from pancreatic ductal adenocarcinoma. The bioinformatic analysis revealed similar sensitivities (64-97.4%), specificities (85–98%) and diagnostic accuracies (86–98%). Furthermore, the results show that DNA hypermethylation of the investigated promoter regions is preserved from primary colorectal carcinoma and pancreatic ductal adenocarcinoma to their liver metastases.
Conclusions
The new methylation biomarker panels exhibit high sensitivity, specificity and diagnostic accuracy and enable successful differentiation between primary and metastatic adenocarcinomas of the liver using methylation-specific digital PCR. A high concordance between methylation-sensitive high-resolution melting analysis, digital PCR and bioinformatic results from publicly available databases was achieved.
AI-driven drug design for short-term anxiety disorder
Authors: S Hari Ram , V Latha , V Gomathi , A Ranichitra , Dhamotharan Varsha , RM Vidhyavathi , D Prabhu 
Published: June 2024

Abstract

Anxiety is the most common neurological disorder and results in cognitive, emotional, and somatic behavioral changes. Anxiety may invoke an unpleasant feeling that is strongly associated with apprehension, fear, and disturbance of daily routine life activities. GABA acts as an inhibitory neurotransmitter within the central nervous system, and a decrease in its levels can result in anxiety. Therefore, GABA-A receptor proteins (PDB ID: 4COF) are suitable targets for drug design. Lorazepam is a commonly used drug for the treatment of short-term anxiety. However, Lorazepam causes serious side effects both physically and mentally during treatment for patients. To alleviate the serious side effects of Lorazepam, in this work, in silico studies based on modern artificial intelligence (AI)-based virtual screening were carried out with a series of computational chemistry methods, such as molecular docking (MD), molecular dynamics simulation (MDS) and quantitative structure–activity relationships (QSAR). Initially, using the MolAICal tool, compounds similar to Lorazepam were generated (M1-M12), and based on drug likeliness, 9 compounds were selected (M1, M4-M7, M9-M12). Then, molecular docking was carried out to analyze and visualize their binding scores with the 4COF protein structure. Compound M12 has a greater binding affinity (i.e., a lower binding energy of -8.276 kcal/mol) than Lorazepam. Its applicability was ascertained via QSAR analysis. A molecular dynamics study of M12 and that of Lorazepam showed that M12 has very good binding to the protein 4COF through multiple H-bond interactions, as more than 100% of the simulation times with the ASP 43 residue and 98% of the simulation times with the GLU155 residue. Various protein‒ligand interactions that lasted more than 48% of the simulation time in the selected trajectory were considered. Analysis of these parameters demonstrated the stable binding of M12 within the binding pocket of 4COF, and M12 had more interactions; hence, M12 was proven to be an alternative drug for treating anxiety with high efficacy.
Pineal cyst apoplexy in a pregnant female. Case Report
Authors: Azab Mohammed. A , Hazim Ahmed , El-Gohary Nour , Mostafa Hamed 
Published: June 2024

Abstract

Background:
Pineal cyst is an uncommon condition in pregnancy. It is often encountered as an incidental finding in brain imaging. Most of pineal cysts are benign and asymptomatic. Bleeding inside these cysts is very rare in pregnancy.
Clinical presentation:
A 30-year-old female patient with no significant past medical history, presented to the emergency department at 36 weeks gestation with an episode of transient unilateral headache. Headache was associated with dizziness and left arm ascending numbness. Neurological examination was normal.
Investigations:
She has a history of a known pineal cyst. CT head was obtained, reviewed and compared to previous scans 7 years ago. It showed that the pineal cyst had a suspected bleeding.
Management:
The patient was admitted to the neurosurgery department for conservative management without any surgery and few days later, symptoms gradually improved.
Follow-up:
Three weeks later, the patient reported spontaneous improvement of the presenting symptoms. The decision was to proceed with continued watchful follow-up and awaiting a caesarian section delivery. Patient returned for follow up three months later without any symptoms. Following delivery, the patient remained asymptomatic and no further problems occurred during the postpartum period.
Conclusion:
Pineal cyst apoplexy is a relatively rare condition and it usually affects young adult females, however, the exact relation to pregnancy and the effect of apoplexy on the course of pregnancy is not well defined.
Analysis of short-term self-healing performance of asphalt mixture under fatigue damage
Authors: Wang Ya , Zhang Liwen , wang xianguang 
Published: June 2024

Abstract

To investigate the self-healing characteristics of fatigue damage in asphalt mixtures, controlled stress bending fatigue tests and self-healing tests were designed to determine the fatigue equation and fatigue damage equation of the mixture. Two indicators based on the theory of dissipated energy and visco-elastic ratio were proposed to evaluate the self-healing performance of asphalt mixtures. The test results showed that, due to the influence of specimens and external factors, even after smoothing, the numerical dispersion of the flexural modulus was still large, making it unsuitable for evaluating the self-healing performance of the mixture. The calculated absolute value and relative value of 50th dissipative energy exhibited a good linear relationship with the damage degree; as the damage increased, the material's recovery from damage also increased. By taking the visco-elastic ratio at 50th loading moment for asphalt mixtures, relative and absolute healing index values were obtained. After an interval of 30 minutes, there was a significant change in initial visco-elastic ratio for small beams, which usually exceeded that of undamaged small beams. This trend became more pronounced as damage increased. when reaching a damage level of 0.4, viscous deformation proportion was more than twice that of undamaged original small beams' visco-elastic ratio.
Genistein inhibited endocytosis and fibrogenesis in transforming growth factor-β1-stimulated keloid via CTGF signaling pathways
Authors: Lu Chun-Te , Ko Jiunn-Liang , Ou Chu-Chyn , Hsu Chih-Ting , Hsiao Yu-Ping , Tang Sheau-Chung 
Published: June 2024

Abstract

Background: This study aimed to evaluate soy isoflavones' effect and potential use—specifically genistein—in treating human keloid fibroblast cell lines (KFs) and in a keloid tissue culture model.
Methods: to investigate the effects of genistein on keloid, a wound-healing assay was performed to detect cell migration. Flow cytometry was used to measure apoptosis. Western blotting and immunofluorescence staining were performed to detect the expression of target proteins. Keloid fibroblast tissues were isolated, cultured, and divided into the control, silenced connective tissue growth factor (CTGF) proteins, and shNC (negative control) groups.
Results: genistein could suppress cell proliferation and migration and enhance apoptosis at the G2/M phase in keloid fibroblasts. Genistein inhibited the expression of collagen 1A1 I, fibronectin, and CTGF proteins, reducing collagen 1A1 accumulation. The expressions of hypoxia-inducible factor-1α (HIF-1α), transforming growth factor-β (TGF-β), and CTGF were reduced after exposure to genistein. The cell migration ability from the keloid patient’s tissues was decreased by genistein treatment and was time-dose dependent. Genistein also abated TGF-β1-induced keloid fibrosis through the endocytosis model. Additionally, genistein could increase the expression of p53 in a dose-dependent manner. Conclusions: This process may depend on the regulation of CTGF. Genistein may attenuate the activity of keloid fibroblasts and reduce keloid formation. The results of our study indicate that genistein-induced p53 undergoes apoptosis through the CTGF pathway in a P53-dependent manner, suggesting that our research provides a new strategy for developing drugs for treating keloids.
Evaluating the Relationship Between News Source Sharing and Political Beliefs
Authors: Pozo Sofía M. del , Pinto Sebastián , Serafino Matteo , Cicchini Tomás , Moss Federico , Makse Hernán A. , Balenzuela Pablo 
Published: June 2024

Abstract

In an era marked by an abundance of news sources, access to information significantly influences public opinion. Notably, the bias of news sources often serves as an indicator of individuals' political leanings. This study explores this hypothesis by examining the news sharing behavior of politically active social media users, whose political ideologies were identified in a previous study. Using correspondence analysis, we estimate the Media Sharing Index (MSI), a measure that captures bias in media outlets and user preferences within a hidden space. During Argentina’s 2019 election on Twitter, we observed a predictable pattern: center-right individuals predominantly shared media from center-right biased outlets. However, it is noteworthy that those with center-left inclinations displayed a more diverse media consumption, which is a significant finding. Despite a noticeable polarization based on political affiliation observed in a retweet network analysis, center-left users showed more diverse media sharing preferences, particularly concerning the MSI. Although these findings are specific to Argentina, the developed methodology can be applied in other countries to assess the correlation between users’ political leanings and the media they share.
Numerical model and coupled vibration analysis of transmission shaft with spatial angle misalignment
Authors: Zhang Bao , Su Xiaoping , Zang Liguo 
Published: June 2024

Abstract

Vibration control is the key to development of high-speed and light-weight transmission system. There are many factors affecting the vibration, and the influence of misalignment is the most obvious. Therefore, it is important to understand the dynamic response of transmission shaft with misalignment. In previous studies, researchers studied the influence of plane angle misalignment. However, there are few researches on the effect of spatial misalignment on shafting vibration. In this paper, a numerical model of shafting with spatial misalignment is established. The influence of plane angle misalignment and spatial angle misalignment on the vibration is studied. The numerical and experimental results show that the vibration of shafting with spatial angle misalignment is bending-torsional coupled vibration, and the two kinds of vibration reinforce each other, and the torsional vibration is the main vibration. Compared with the influence of plane angle misalignment, the influence of spatial angle misalignment is more obvious..
Semi-Supervised Dimensionality Reduction Method Utilizing Pairwise Constraints and Integrating Similarity and Dissimilarity among Data
Authors: Liu Zixuan , Luo Rong 
Published: June 2024

Abstract

Data preprocessing stages, including data reconstruction and dimensionality reduction, play a pivotal role in influencing subsequent machine learning and data mining endeavors. While supervised dimensionality reduction typically surpasses unsupervised methods through direct label exploitation, the scarcity or high acquisition cost of labeled data in practical scenarios has fueled interest in semi-supervised alternatives. These methodologies ingeniously integrate sparse labeled and abundant unlabeled data, to aid data representation and dimensionality reduction.This study introduces a novel nonlinear semi-supervised dimensionality reduction algorithm, which employs pairwise constraints (must-link and cannot-link) and radial basis functions to obtain similarity and dissimilarity among data points. Leveraging spectral decomposition, our algorithm aims to reconstruct the initial data, thereby exposing intricate nonlinear patterns obscured within high-dimensional datasets. Compared to traditional semi-supervised algorithms, a series of experiments based on real data have verified the effectiveness of the proposed method.
Quantum-Inspired Clustering for Hazardous Asteroid Prediction in Quantum Machine Learning
Authors: Bhagwakar Priya P. , Thaker Chirag Suryakant , Joshiara Hetal A. 
Published: June 2024

Abstract

An asteroid impact is one of the rare natural disasters that can be prevented or mitigated using the proper preparation and preparatory measures. The main goal is to investigate the use of quantum machine learning (QML) in the context of asteroid prediction in order to improve early detection and trajectory forecasting capabilities. New computational approaches are necessary in the dynamic field of astronomical hazard assessment, and QML offers itself as an advanced paradigm to meet the challenges of this important task. In this study, we evaluate the EQIE-FCM (Enhanced Quantum-Inspired Evolutionary Fuzzy C-Means) clustering algorithm and compare it with other models such as K-Medoid, Spectral Clustering, Fuzzy C-Means, Quantum K-Means, and Quantum Fuzzy C-Means. EQIE-FCM outperforms these models, surpassing Silhouette and Davies-Bouldin thresholds. The choice of clustering algorithm depends on data characteristics and problem context. By leveraging quantum computing to evolve crucial parameters, EQIE-FCM effectively clusters datasets. We evaluate its efficacy using different-sized asteroid datasets. Quantum machine learning shows promise for accurate predictions of hazardous asteroids, but its integration requires awareness of both strengths and limitations.
Rihla: A Tourism Chatbot System Powered by Generative AI for Riyadh and AlUla
Authors: Aref Badriyah , Alamri Nawal , Alshehri Arwa , Alyousef Sadeem , Alnaim Norah 
Published: June 2024

Abstract

International tourism has increased by 121% since July 2022, driven by efforts to fulfil Saudi Vision 2030 and capitalize on an AI-driven economy. With AI revolutionizing the tourism and travel sectors, Chatbots have emerged as popular tools, leveraging AI and natural language processing (NLP) to automate responses and enhance user experiences. This study addresses Saudi Vision 2030’s objectives by introducing an intelligent Chatbot for improved tourism experiences in Saudi Arabia. Through integrating the text-divinci-002 model with Flask, the Chatbot delivers prompt and precise responses, catering to tourists’ inquiries. The findings demonstrate its high usability and utility in assisting travelers. This research aims to contribute the ongoing advancements in AI-driven tourism, aligning with the broader vision of transforming Saudi Arabia’s tourism industry.
Estimation of Human Age using Machine Learning on Panoramic Radiographs: A Pilot Study for Brazilian Patients
Authors: Oliveira Willian , Albuquerque Mariana , Burgardt Caio Augusto Pereira , Pontual Maria Luiza dos Anjos , Zanchettin Cleber 
Published: June 2024

Abstract

This paper addresses a relevant problem in Forensic Sciences by integrating radiological techniques with cutting-edge machine learning methodologies to create a non-invasive, efficient, and less examiner-dependent approach for age estimation. We also present a new dataset composed of 12,827 dental panoramic X-ray images that reflect the specific demographic characteristics of the Brazilian population. The proposed approach achieved robust and reliable results, achieving a Test Mean Absolute Error of 3.1 years and an R-squared value of 95.5%. Professional radiologists have validated that our model focuses on critical features for age assessment used in odontology, including pulp chamber dimensions and stages of permanent teeth calcification, even in edentulous cases. The model also relies on information from the mandible, maxillary sinus, and vertebrae, indicating a wide range of anatomical features for decision-making. This study demonstrates the significant potential of AI to revolutionize age estimation in Forensic Science, offering a more accurate, efficient, and universally applicable solution.
Evolution of C-point singularity and polarization coverage of Poincare-Bessel beam in self-healing process
Authors: Kumar Subith , Pal Anupam , Shiri Arash , Samanta Goutam K , Gbur Greg 
Published: June 2024

Abstract

As a vector version of scalar Bessel beams, Poincare-Bessel beams (PBBs) have attracted a great deal of attention due to their non-diffracting and self-healing properties as well as the presence of polarization singularities. Previous studies of PBBs have focused on cases that consist of a superposition of Bessel beams in orthogonal circular polarization states; here, we present a theoretical and experimental study of PBBs for which the polarization states are taken to be linear, which we call a linear PBB. Using a mode transformation of a full Poincare beam constructed from linear polarization states, we observe the linear PBB as providing an in principle infinite number of covers of the Poincare sphere in a transverse plane and with an infinite number of C-points with positive and negative topological indices. We also study the dynamics of C-point singularities in a linear PBB in the process of self-healing after being obstructed by an obstacle, providing insight into ''Hilbert Hotel'' style evolution of singularities in light beams. The present study can be useful for imaging in the presence of depolarizing surroundings, studying turbulent atmospheric channels, and exploring the rich mathematical concepts of transfinite numbers.