bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predictors of Secondary Revascularization after Coronary Artery Bypass Graft Surgery and Role of Dual Antiplatelet Therapy
Authors: Ch Iftikhar Ali , Nasir Khurram , Chaudhry Azhar , Wu Pei-Tzu , Siddique Muhammad , Ullah Raja , Tahirkheli Mashal , Qadar Abdul , Weitzel Hunter , MBBS Rahat Jamal , Tahirkheli Naeem 
Published: December 2024

Abstract

Background: Despite advancements in surgical techniques, interventional procedures, novel pharmacotherapies, and other contemporary treatments, patients’ post-CABG remain at risk for graft failure and progression of native CAD (4). Consequently, secondary revascularization is often required, with PCI being the preferred method
Methods: This is a retrospective observational study evaluating the incidence, trends, and predictors of revascularization after CABG surgery. Antiplatelet therapy and its impact on revascularization after CABG were analyzed.
Results: Of 2,476 patients followed in this post-CABG study, the analysis included 1,006 patients who received AMT and 770 patients who received DAPT for six months or more after surgery. The survival rates were 92.0% for AMT and 96.5% for the DAPT group (odds ratio (OR)=0.421, 95% confidence interval (95% CI): 0.269-0.658; p<0.001). In patients who received DAPT after CABG, a significantly higher incidence of revascularization was noted, compared to AMT (22.08% vs 6.96%; OR=3.157, 95% CI: 2.734-4.940; p<0.001). The binary regression model revealed that younger patients (HR=0.964, 95% CI: 0.95-0.97; p <0.001), diabetics (HR=1.50, 95% CI: 1.12-2.00, p=0.007), patients who had fewer internal mammary artery grafts (HR=0.54, 95% CI: 0.36-0.81, p=0.003), and patients receiving DAPT of any duration after CABG (HR=3.47, 95% CI: 2.55-4.72, p<0.001) were more likely to receive revascularization after CABG (Table 2). The model, comprising these four predictors, was able to explain 12.8% of the variance in post-CABG revascularization (Nagelkerke R² = 0.128; p < 0.001).
Conclusion: Diabetes mellitus, younger age, fewer IMA grafts, and the use of DAPT after CABG were strong predictors of the need for secondary revascularization
GBA1 mutations alter neuronal excitability and ultrastructure in Parkinson´s disease, regulating VGLUT2 and CRYAB in dopaminergic neurons
Authors: Rodríguez-Traver Eva , Suárez Luz M. , Crespo Carlos , González-Burgos Irene , Vecino Rebeca , Jurado-Coronel Juan C. , Galán María , González-González Marta , Díaz-Guerra Eva , Moratalla Rosario , Vicario Carlos 
Published: December 2024

Abstract

Mutations in the glucocerebrosidase 1 (GBA1) gene are major risk factors for Parkinson´s disease (PD), but their role in PD etiopathology is not fully understood. The impact of GBA1 mutations on neuronal maturation, function and degeneration was investigated in dopaminergic (DA) neurons obtained from induced pluripotent stem cells (iPS cells/iPSCs) derived from PD patients carrying the heterozygous N370S or L444P mutation in GBA1. DA neurons co-expressing TH and VGLUT2 were detected in the cultures, and their number and/or expression of VGLUT2/SLC17A6 mRNA was markedly reduced in both N370S and L444P cultures compared to controls. Electrophysiological recordings revealed a significant increase in the firing rate of N370S but not L444P neurons, whereas evoked dopamine release was stronger from neurons carrying either mutation than from the controls. Furthermore, there was a significant accumulation of α-synuclein aggregates in the cell body and dendrites of N370S neurons. Remarkably, neurons carrying either GBA1 mutation accumulated abundant Lewy body-like inclusions, multilamellar bodies, Golgi apparatus vacuolated dictyosomes and autophagosomes. Notably, a significant upregulation of the chaperone CRYAB/HSPB5/alpha-crystallin-B was found early in DA neuron differentiation and in the substantia nigra of PD patients. Therefore, our cellular model allows clear features of neurodegeneration to be detected in neurons derived from PD patients. Our findings indicate that N370S and L444P GBA1 mutations impair midbrain DA neurons expressing VGLUT2, and provoke molecular, functional and ultrastructural changes, possibly involved in PD etiopathology. They suggest that VGLUT2 and CRYAB may potentially serve as early molecular targets and/or biomarkers in GBA1-PD.
A fast convolution-based method for peridynamic models in plasticity and ductile fracture
Authors: Mousavi Farzaneh , Jafarzadeh Siavash , Bobaru Florin 
Published: December 2024

Abstract

We introduce the fast convolution-based method (FCBM) for a peridynamic correspondence (cPD) model to simulate finite plastic deformations and ductile fracture in 3D. The cPD model allows the direct use of classical finite plasticity constitutive ductile failure models, like the Johnson-Cook (J-C) model used here. We validate the FCBM for the cPD model against experimental results from the literature on ductile failure in Al2021-351 alloy samples of various geometries. Notably, calibration of elastic and hardening material parameters is made only using the experimental data from the simplest geometry, a smooth round bar, and only up to the necking point. We then use that calibrated model beyond necking, through full failure, and for all the different sample geometries. The performance (speedup and memory allocation) of the new method is compared versus the meshfree method normally used to discretize PD models for fracture and damage. The proposed method leads to efficient large-scale peridynamic simulations of finite plastic deformations and ductile failure that are closer to experimental measurements in terms of displacement and plastic strain at failure than previous FEM-based solutions from the literature.
Elaboration of Novel Biocomposite Hydrogel Polymers made of Alginate and Sepiolite and endowed with Enhanced Properties
Authors: BAZIZ Meriem , KAMECHE Mostefa , BENHARRATS Nassira , HU Liran , REMITA Samy 
Published: December 2024

Abstract

Nowadays growing attention is given to the design and development of novel interpenetrating polymer networks (IPN) from the combination of hydrogel polymers loaded with natural clay. In this work, we used the eco-friendly IPN strategy to develop novel hydrogel biocomposite beads, made of alginate (ALG), with improved clay dispersion, higher pH sensitivity, better stretchability and swellability, together with enhanced regenerability properties and biodegradability resistance. Fibrous clay, namely sodium sepiolite (NaS), was loaded into alginate simple biocomposite network (SBN) beads, via manual co-grinding mixture/encapsulation method, at different sepiolite loads. Alginate double biocomposite network (DBN) beads were also prepared at different sepiolite loads, via the diffusion of acrylamide monomer (AAM) inside alginate single biocomposite network (SBN) beads, followed by in situ free radical polymerization of AAM into poly-acrylamide (pAAM), using ammonium persulfate (APS) as polymerization initiator and N,N-methylenebisacrylamide (Bis) as covalent crosslinker agent. The as-elaborated SBN and DBN beads were then characterized by digital camera recording, XRD analysis, ATR-FTIR characterization and SEM observation. FTIR results showed that NaS and pAAM were successfully incorporated into DBN beads, whilst XRD analysis revealed the enhancement of fibrous clay dispersion, even at relatively high sepiolite loads. Besides, SEM microscopy confirmed the porous spongious nature of DBN beads. The properties of the as-elaborated SBN and DBN beads were also evaluated by test touching, swelling rate measurements, adsorption/desorption experiments and biodegradability evaluation. DBN beads properties were always found enhanced in comparison with those of SBN beads: very good stretchability, good swelling behavior and stability in water whatever the pH, either in acidic or alkaline solution, enhanced adsorption/desorption properties towards methylene blue (MB) dye, very good regenerability and delayed biodegradability. In summary, this work showed an interesting and safe IPN/biocomposite approach to develop high-performance alginate biocomposite polymers as a promising system towards their use in eco-friendly processes.
Document embeddings for long texts from Transformers and Autoencoders
Authors: Christou Lenos , Bompotas Agorakis , Makris Christos 
Published: December 2024

Abstract

In document categorization, the escalating volume of digital data underscores the critical need for advanced techniques in generating semantically rich document embedding, particularly for topic modelling applications. This article presents a novel methodology that leverages the capabilities of Sentence-BERT (SBERT) for sentence embedding, aiming to address the challenges associated with embedding longer texts. The process begins by decomposing documents into individual sentences that can be processed using the SBERT model which generates an embedding for each sentence. Subsequently, a clustering algorithm is employed to select representative sentence embeddings for each document. These embeddings serve as the foundation for constructing comprehensive document embeddings through an autoencoder. This research exclusively explores the autoencoder approach, discarding alternative methods for brevity and focus. The autoencoder strategy showed promising results, occasionally outperforming the base model, Doc2Vec, in specific scenarios. This highlights the method's potential effectiveness in document embedding tasks where understanding long context is important. Moreover, when the Transformer Autoencoder was fine-tuned on test data, it achieved performance comparable to that of Doc2Vec, underscoring the viability of this approach. The findings suggest considerable room for improvement in various aspects of the methodology, including the clustering process and the encoder architecture. This article underscores the potential of autoencoders in advancing the state-of-the-art in document embedding technologies, setting the stage for further refinement and exploration.
Robust Audio-Image Steganography using Cross-Modal Based Transformer Models
Authors: Taremwa Mark , Anaedevha Roger Nick , Trofimov Alexander Genadievich 
Published: December 2024

Abstract

This research investigates the use of Vision Transformers (ViT), Audio Spectrogram Transformers (AST), and Cross-Modal Transformers (CMT) in audio-image fusion tasks, aiming to improve the representation learning and interaction between auditory and visual data. The ViT model extracts visual features from image patches resized to 224x224 pixels, while the AST model converts audio signals into mel spectrograms to capture detailed auditory features. The central focus is on the robust CMT model, which integrates visual and auditory features through a cross-modal attention mechanism. Extensive experiments using a diverse audio-image dataset from Kaggle reveal significant improvements. The initial developed ViT model enhances image embedding capacity by 12%, the AST model improves audio embedding tasks by 15%, and the CMT model achieves and overall embedding capacity increased by an average of 58.7%, an image PSNR improved by an average of 57.5%, image MSE reduced by an average of 87.3% as the CMT model shows more consistent performance across all the different stegos. this enhancement in cross-modal retrieval tasks, highlighting the effectiveness of robust CMT model in learning and utilizing inter-modal relationships. The proposed robust cross-modal attention mechanism outperforms traditional ViT model and Least Significant Bits [LSB] concatenation algorithms in feature alignment accuracy. Ablation studies further validate the robustness of this approach, demonstrating the contribution of each component to overall performance. This research establishes the viability and superiority of transformer-based architectures in audio-image fusion tasks, suggesting potential advancements in cross-modal tasks like audio-visual synchronization and multimodal sentiment analysis.
Interpretable machine learning classifiers implicate GPC6 in Parkinson’s disease from single-nuclei midbrain transcriptomes
Authors: Farhan Sali , Fiorini Michael , Li Jialun , Fon Edward , Thomas Rhalena 
Published: December 2024

Abstract

Parkinson’s disease (PD) is a progressive and devastating neurodegenerative disease. An incomplete understanding of its genetic architecture remains a major barrier to the clinical translation of targeted therapeutics, necessitating novel approaches to uncover elusive genetic determinants. Single-cell and single-nuclear RNA sequencing (scnRNAseq) can help bridge this gap by profiling individual cells for disease-associated differential gene expression and nominating genes for targeted genomic analyses. Here, we introduce a machine learning framework to identify molecular features that characterize post-mortem brain cells from PD patients. We train classifiers to distinguish between PD and healthy cells, then decode the models to unravel the ‘reasons’ behind the classifications, revealing key genes expression signatures that characterize cells from the parkinsonian brain. Application of this framework to three publicly available snRNAseq datasets characterizing the post-mortem midbrain identified cell-type-specific gene sets that accurately classify PD cells across all datasets, demonstrating our approach's capacity to identify robust molecular markers of disease. Targeted genomic analyses of the key genes characterizing PD cells revealed a previously undescribed association between PD and rare variants in GPC6, a member of the heparan sulfate proteoglycan family, which have been implicated in the intracellular accumulation of α-synuclein preformed fibrils. We replicate this association in three separate case-control cohorts. Our method promises to enhance understanding of the genetic architecture in complex diseases like PD, representing a critical step toward targeted therapeutics. Our publicly available framework is readily applicable across diseases.
Multi-ancestry genome-wide association study of severe pregnancy nausea and vomiting identifies risk loci associated with appetite, insulin signaling, and brain plasticity
Authors: Fejzo Marlena , Wang Xinran , Zöllner Julia , Gualdo Natàlia Pujol , Laisk Triin , Finer Sarah , Heel David van , Team Genes & Health Research , Brumpton Ben , Bhatta Laxmi , Hveem Kristian , Jasper Elizabeth , Edwards Digna Velez , Hellwege Jacklyn , Edwards Todd , Jarvik Gail , Luo Yuan , Khan Atlas , MacGibbon Kimber , Gao Yuan , Ge Gaoxiang , Averbukh Inna , Soon Erin , Angelo Mike , Magnus Per , Vaudel Marc , Shu Chang , Mancuso Nicholas , Team Estonian Biobank Research 
Published: December 2024

Abstract

While most pregnancies are affected by nausea and vomiting, hyperemesis gravidarum (HG) is at the severe end of the clinical spectrum and is associated with dehydration, undernutrition, and adverse maternal, fetal, and child outcomes. Herein we performed a multi-ancestry genome-wide association study (GWAS) of severe nausea and vomiting of pregnancy of 10,974 cases and 461,461 controls across European, Asian, African, and Latino ancestries. We identified ten significantly associated loci, of which six were novel (SLITRK1, SYN3, IGSF11, FSHB, TCF7L2, and CDH9), and confirmed previous genome-wide significant associations with risk genes GDF15, IGFBP7, PGR, and GFRAL. In a spatiotemporal analysis of placental development, GDF15 and TCF7L2 were expressed primarily in extra villous trophoblast, and using a weighted linear model of maternal, paternal, and fetal effects, we confirmed opposing effects for GDF15 between maternal and fetal genotype. Conversely, IGFBP7 and PGR were primarily expressed in developing maternal spiral arteries during placentation, with effects limited to the maternal genome. Risk loci were found to be under significant evolutionary selection, with the strongest effects on nausea and vomiting mid-pregnancy. Selected loci were associated with abnormal pregnancy weight gain, pregnancy duration, birth weight, head circumference, and pre-eclampsia. Potential roles for candidate genes in appetite, insulin signaling, and brain plasticity provide new pathways to explore etiological mechanisms and novel therapeutic avenues.
Relationship of Early Life Adversity to Moral Development and Psychopathology among Children and Adolescents: A Cross-Sectional Study
Authors: Khurana Priyal , Singh Ram , Galvin Matthew , Gaffney Margaret , Gupta Mayank 
Published: December 2024

Abstract

Introduction
Empirical evidence suggests early adverse life experiences are linked to delays in moral development. This study aims to assess the correlation between PI and delayed conscience formation in moral development.
Methods
The study included 125 semi-structured interviews with youth who experienced adverse childhood experiences and compared their conscience development with youth raised in relatively advantaged environments. Conducted in two phases, the first phase used a two-sample z-test to compare distress indicators of conscience impairment between groups. In the second phase, cases were analyzed using prototypical vignettes and conscience development quotient scores. The severity of psychopathological interference was assessed using behavioral ratings and DSM categorical diagnoses. Multiple linear regression examined the association between conscience development quotient and severity of psychopathological interference, including six covariates. A similar regression model was used to assess the association between psychopathological interference and clinical global assessment of functioning scores using the same covariates.
Results
Findings suggest severity of psychopathological interference, presence of other mental health conditions, onset of adverse life experiences to play a role in conscience development.
Discussion
The future implications suggest a humanistic approach to seek insights into moral development and present an alternative of global assessment of functioning that was discontinued because of its shortcomings, which conscience development quotient can bridge.
Nyugdíjasok rekreációja és szabadidő felhasználásának időbeli összehasonlító elemzése
Authors: Tessényi Judit 
Published: December 2024

A kutatás célja a nyugdíjas korúak életmódjának és szabadidős tevékenységeinek jobb megértése, és az eredmények összesített feldolgozása. Némileg meglepő módon jelentősen javult a nyugdíjasok jólléte és életminősége - a mért mutatók mentén, a megkérdezettek körében - az előző, 8 évvel korábban mért adatokhoz képest. A korábbi kutatások rámutattak arra, hogy az aktív szabadidős tevékenység számos előnnyel járhat, mint például az egészség javítása és a társas kapcsolatok építése. Azonban sok idős embernek hiányzik a külső vagy belső ösztönzés a fizikai aktivitás, hobbi vagy társas kapcsolatok fenntartásához, ami befolyásolhatja jólétüket és élettel való elégedettségüket. A korábbi kutatásunk során hat fő témakört azonosítottunk, amelyek kulcsfontosságúak az idősek szabadidejének megértéséhez, és ezen alapulva 2024-ben ismétlő kutatást végeztünk a nyugdíjasok tevékenységeinek felmérésére. Ennek során fontosnak bizonyult az aktívitás, életkörülmények, egészség, motiváció, napi teendők és egyéb tényezők vizsgálata. A mostani válaszadók rendszeresen végeznek testmozgást, aktívan részt vesznek szellemi tevékenységekben, és egyre többen használnak technológiai eszközöket a társas kapcsolatok és a szabadidős tevékenységek szervezése céljából. A változásokat számszerűsítettük, amely az idős emberek preferenciáit mutatja a különböző tevékenységek terén az eltelt időszak alatt.
Pros and Cons of Cardiovascular Herbal Therapy: Molecular Docking, ADMET, Physiological and Pharmacological Significance
Authors: Kadi Mounime , Berraouaan Ali , Ziyyat Abderrahim , Mekhfi Hassane , Bnouham Mohamed , Legssyer Abdelkhaleq 
Published: December 2024

Introduction:
For a long period, traditional medicine has held a crucial role in maintaining
cardiovascular homeostasis. However, very few scientific studies have investigated and reported
information on the mechanism by which these plants act through their active ingredients. Presently,
there is consideration for utilizing computer-assisted methods to incorporate predictive and dependable
data in addition to experimental findings.

Objective:
The objective of this review article was to furnish information on medicinal plant extracts
that have undergone experimental testing to assess their cardioprotective properties

Methods:
Thus, eleven phytomolecules have been chosen based on their bioactivity scores and their
belonging to medicinal plants frequently used in traditional medicine. Molecular docking analyses
were carried out using Autodock Vina v1.5.7, and were performed to research the molecular pathway
attributed to the effects of phytoconstituents extracted from medicinal plants known for their therapeutic
effects against cardiovascular alterations. Computer ADME/toxicity studies were also performed
to estimate the physiological and pharmacological signification of each phytomolecule.

Results:
The results showed that selected phytomolecules exert considerable therapeutic potential on
different cardiovascular levels through activation, inhibition, and modulation of cellular factor's expressions,
all leading to cardiac muscle protection against stressful attacks. ADMET analysis showed
that all phytomolecules selected responded to drug-likeness according to Lipinski's rule of five and
the possibility of developing medicines, taking into account the dose used for each phytoconstituent.

Conclusion:
Our study demonstrated that various medicinal plants possess significant therapeutic
potential at multiple cardiovascular levels through a series of vital processes, including activation,
inhibition, and modulation of diverse cellular component expression.
Exploration of the Potential Mechanism of Sedum sarmentosu Bunge in the
Treatment of Hepatic Fibrosis Based on Network Pharmacology,
Molecular Docking, and Molecular Dynamics Simulation
Authors: He Wenfei , Tang Yao , Chen Jialin , Chai Yu , Xiong Lingyue , Zhangwei Wanqi 
Published: December 2024

Background:
Sedum sarmentosu Bunge (SSB), a perennial herb, exhibits notable therapeutic
effects on hepatic fibrosis (HF). However, the mechanism of treatment has not been fully determined.

Objective:
The objective of this study is to explore the active components in SSB and investigate its
molecular mechanism of action in the treatment of HF based on network pharmacology, molecular
docking, and molecular dynamics simulation (MD).

Methods:
Databases such as TCMSP, Gene Cards, OMIM, and DAVID, as well as Cytoscape, AutoDock
Vina, and Gromacs software, were used for analysis.

Results:
A total of 5 active components and 86 HF-related targets were screened for SSB, among
which the most prominent components are luteolin and quercetin. The key targets for HF are MMP2,
MMP3, MMP9, ABCG2, etc. GO enrichment analysis showed that SSB was closely associated with
apoptosis, inflammatory response and cell migration processes. KEGG enrichment analysis showed
that the major enrichment pathways for liver fibrosis include EGFR tyrosine kinase inhibitor resistance,
PI3K-Akt signaling pathway, and cancer-related pathways. Molecular docking and MD
showed that luteolin and quercetin have good affinity and stable binding to MMP2, MMP3, and
MMP9.

Conclusion:
SSB exerts therapeutic effects on HF through multiple components, targets, and pathways,
thereby providing a theoretical foundation for the development of its active compounds and
mechanisms of action.