bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamics, circuit design, feedback control of a new hyperchaotic system and its application in audio encryption
Authors: Fu ShiMing , Cheng XueFeng , Liu Juan 
Published: November 2023

AbstractIn this study, a 4D hyperchaotic system is constructed based on the foundation of a 3D Lü chaotic system. The newly devised hyperchaotic system possesses a sole equilibrium point, showcasing a simplified system structure that reduces complexity. This simplification offers a clearer opportunity for in-depth analysis of dynamic behaviors in the realm of scientific research. The proposed hyperchaotic system undergoes an in-depth examination of its dynamical characteristics, including chaotic attractors, equilibrium point stability, Lyapunov exponents’ spectrum, and bifurcation diagram. Numerical analysis results reveal that the attractor of this hyperchaotic system exhibits highly complex, non-periodic, and fractal structural dynamics. Its motion demonstrates extreme sensitivity and randomness, even within a wide range of variations in parameter d, affirming its hyperchaotic properties with two positive Lyapunov exponents. Hyperchaotic bifurcation diagrams typically exhibit highly intricate structures, such as fractals, branches, and period doubling characteristics, signifying that even minor parameter adjustments can lead to significant changes in system behavior, presenting diversity and unpredictability. Subsequently, to further investigate the practical utility of this hyperchaotic system, a linear feedback control strategy is implemented. Through linear feedback control, the hyperchaotic system is stabilized at its unique equilibrium point. Experimental validation is conducted using both computer software simulation Matlab, electronic circuit simulation Multisim, and embedded hardware STM32. The results of these experiments consistently align, providing theoretical support for the application of this hyperchaotic system in practical domains. Finally, leveraging the hyperchaotic keys generated by this hyperchaotic system, audio encryption is achieved using a cross-XOR algorithm, which is then realized on the embedded hardware platform STM32. The results show that the audio encryption scheme based on the hyperchaotic system is feasible, and the method is simple to implement, has nonlinear characteristics and certain algorithm complexity, which can be applied to audio encryption, image encryption, video encryption, and more.
Prognostic association supports indexing size measures in echocardiography by body surface area
Authors: Fung Angus S. Y. , Soundappan Dhnanjay , Loewenstein Daniel E. , Playford David , Strange Geoffrey , Kozor Rebecca , Otton James , Ugander Martin 
Published: November 2023

AbstractBody surface area (BSA) is the most commonly used metric for body size indexation of echocardiographic measures, but its use in patients who are underweight or obese is questioned (body mass index (BMI) < 18.5 kg/m2 or ≥ 30 kg/m2, respectively). We aim to use survival analysis to identify an optimal body size indexation metric for echocardiographic measures that would be a better predictor of survival than BSA regardless of BMI. Adult patients with no prior valve replacement were selected from the National Echocardiography Database Australia. Survival analysis was performed for echocardiographic measures both unindexed and indexed to different body size metrics, with 5-year cardiovascular mortality as the primary endpoint. Indexation of echocardiographic measures (left ventricular end-diastolic diameter [n = 230,109] and mass [n = 224,244], left atrial volume [n = 150,540], aortic sinus diameter [n = 90,805], right atrial area [n = 59,516]) by BSA had better prognostic performance vs unindexed measures (underweight: C-statistic 0.655 vs 0.647; normal weight/overweight: average C-statistic 0.666 vs 0.625; obese: C-statistic 0.627 vs 0.613). Indexation by other body size metrics (lean body mass, height, and/or weight raised to different powers) did not improve prognostic performance versus BSA by a clinically relevant magnitude (average C-statistic increase ≤ 0.02), with smaller differences in other BMI subgroups. Indexing measures of cardiac and aortic size by BSA improves prognostic performance regardless of BMI, and no other body size metric has a clinically meaningful better performance.
Inflammatory bowel disease biomarkers revealed by the human gut microbiome network
Authors: Hu Mirko , Caldarelli Guido , Gili Tommaso 
Published: November 2023

AbstractInflammatory bowel diseases (IBDs) are complex medical conditions in which the gut microbiota is attacked by the immune system of genetically predisposed subjects when exposed to yet unclear environmental factors. The complexity of this class of diseases makes them suitable to be represented and studied with network science. In this paper, the metagenomic data of control, Crohn’s disease, and ulcerative colitis subjects’ gut microbiota were investigated by representing this data as correlation networks and co-expression networks. We obtained correlation networks by calculating Pearson’s correlation between gene expression across subjects. A percolation-based procedure was used to threshold and binarize the adjacency matrices. In contrast, co-expression networks involved the construction of the bipartite subjects-genes networks and the monopartite genes-genes projection after binarization of the biadjacency matrix. Centrality measures and community detection were used on the so-built networks to mine data complexity and highlight possible biomarkers of the diseases. The main results were about the modules ofBacteroides, which were connected in the control subjects’ correlation network,Faecalibacterium prausnitzii, where co-enzyme A became central in IBD correlation networks andEscherichia coli, whose module has different patterns of integration within the whole network in the different diagnoses.
Modelling opinion dynamics under the impact of influencer and media strategies
Authors: Helfmann Luzie , Djurdjevac Conrad Nataša , Lorenz-Spreen Philipp , Schütte Christof 
Published: November 2023

AbstractDigital communication has made the public discourse considerably more complex, and new actors and strategies have emerged as a result of this seismic shift. Aside from the often-studied interactions among individuals during opinion formation, which have been facilitated on a large scale by social media platforms, the changing role of traditional media and the emerging role of “influencers” are not well understood, and the implications of their engagement strategies arising from the incentive structure of the attention economy even less so. Here we propose a novel framework for opinion dynamics that can accommodate various versions of opinion dynamics as well as account for different roles, namely that of individuals, media and influencers, who change their own opinion positions on different time scales. Numerical simulations of instances of this framework show the importance of their relative influence in creating qualitatively different opinion formation dynamics: with influencers, fragmented but short-lived clusters emerge, which are then counteracted by more stable media positions. The framework allows for mean-field approximations by partial differential equations, which reproduce those dynamics and allow for efficient large-scale simulations when the number of individuals is large. Based on the mean-field approximations, we can study how strategies of influencers to gain more followers can influence the overall opinion distribution. We show that moving towards extreme positions can be a beneficial strategy for influencers to gain followers. Finally, our framework allows us to demonstrate that optimal control strategies allow other influencers or media to counteract such attempts and prevent further fragmentation of the opinion landscape. Our modelling framework contributes to a more flexible modelling approach in opinion dynamics and a better understanding of the different roles and strategies in the increasingly complex information ecosystem.
Expression of a large coding sequence: Gene therapy vectors for Ataxia Telangiectasia
Authors: Hirch Tanja , Brander Nadine , Schenk Franziska , Pöllmann Simon J. , Reichenbach Janine , Schubert Ralf , Modlich Ute 
Published: November 2023

AbstractAtaxia telangiectasia is a monogenetic disorder caused by mutations in the ATM gene. Its encoded protein kinase ATM plays a fundamental role in DNA repair of double strand breaks (DSBs). Impaired function of this kinase leads to a multisystemic disorder including immunodeficiency, progressive cerebellar degeneration, radiation sensitivity, dilated blood vessels, premature aging and a predisposition to cancer. Since allogenic hematopoietic stem cell (HSC) transplantation improved disease outcome, gene therapy based on autologous HSCs is an alternative promising concept. However, due to the large cDNA of ATM (9.2 kb), efficient packaging of retroviral particles and sufficient transduction of HSCs remains challenging.We generated lentiviral, gammaretroviral and foamy viral vectors with a GFP.F2A.Atm fusion or a GFP transgene and systematically compared transduction efficiencies. Vector titers dropped with increasing transgene size, but despite their described limited packaging capacity, we were able to produce lentiviral and gammaretroviral particles. The reduction in titers could not be explained by impaired packaging of the viral genomes, but the main differences occurred after transduction. Finally, after transduction of Atm-deficient (ATM-KO) murine fibroblasts with the lentiviral vector expressing Atm, we could show the expression of ATM protein which phosphorylated its downstream substrates (pKap1 and p-p53).
Nuclear overexpression of DNA damage-inducible transcript 4 (DDIT4) is associated with aggressive tumor behavior in patients with pancreatic tumors
Authors: Tajik Fatemeh , Fattahi Fahimeh , Rezagholizadeh Fereshteh , Bouzari Behnaz , Babaheidarian Pegah , Baghai Wadji Masoud , Madjd Zahra 
Published: November 2023

AbstractDNA damage-inducible transcript 4 (DDIT4) is induced in various cellular stress conditions. Several studies showed that the dysregulation of DDIT4 is involved in different malignancies with paradoxical expressions and roles. Therefore, this study investigated the clinical significance, prognostic, and diagnostic value of DDIT4 in different types of pancreatic tumors (PT). The expression of DDIT4 and long non-coding RNA (TPTEP1) in mRNA level was examined in 27 fresh PT samples using Real-time quantitative PCR (RT-qPCR). Moreover, 200 formalin-fixed paraffin-embedded PT tissues, as well as 27 adjacent normal tissues, were collected to evaluate the clinical significance, prognostic, and diagnosis value of DDIT4 expression by immunohistochemistry (IHC) on tissue microarrays (TMA) slides. The results of RT-qPCR showed that the expression of DDIT4 in tumor samples was higher than in normal samples which was associated with high tumor grade (P = 0.015) and lymphovascular invasion (P = 0.048). Similar to this, IHC findings for nucleus, cytoplasm, and membrane localization showed higher expression of DDIT4 protein in PT samples rather than in nearby normal tissues. A statistically significant association was detected between a high level of nuclear expression of DDIT4 protein, and lymphovascular invasion (P = 0.025), as well as advanced TNM stage (P = 0.034) pancreatic ductal adenocarcinoma (PDAC) and in pancreatic neuroendocrine tumor (PNET), respectively. In contrast, a low level of membranous expression of DDIT4 protein showed a significant association with advanced histological grade (P = 0.011), margin involvement (P = 0.007), perineural invasion (P = 0.023), as well as lymphovascular invasion (P = 0.005) in PDAC. No significant association was found between survival outcomes and expression of DDIT4 in both types. It was found that DDIT4 has rational accuracy and high sensitivity as a diagnostic marker. Our results revealed a paradoxical role of DDIT4 expression protein based on the site of nuclear and membranous expression. The findings of this research indicated that there is a correlation between elevated nuclear expression of DDIT4 and the advancement and progression of disease in patients with PT. Conversely, high membranous expression of DDIT4 was associated with less aggressive tumor behavior in patients with PDAC. However, further studies into the prognostic value and biological function of DDIT4 are needed in future studies.
Glucose restriction in Saccharomyces cerevisiae modulates the phosphorylation pattern of the 20S proteasome and increases its activity
Authors: Bicev Renata Naporano , de Souza Degenhardt Maximilia Frazão , de Oliveira Cristiano Luis Pinto , da Silva Emerson Rodrigo , Degrouard Jéril , Tresset Guillaume , Ronsein Graziella Eliza , Demasi Marilene , da Cunha Fernanda Marques 
Published: November 2023

AbstractCaloric restriction is known to extend the lifespan and/or improve diverse physiological parameters in a vast array of organisms. In the yeast Saccharomyces cerevisiae, caloric restriction is performed by reducing the glucose concentration in the culture medium, a condition previously associated with increased chronological lifespan and 20S proteasome activity in cell extracts, which was not due to increased proteasome amounts in restricted cells. Herein, we sought to investigate the mechanisms through which glucose restriction improved proteasome activity and whether these activity changes were associated with modifications in the particle conformation. We show that glucose restriction increases the ability of 20S proteasomes, isolated from Saccharomyces cerevisiae cells, to degrade model substrates and whole proteins. In addition, threonine 55 and/or serine 56 of the α5-subunit, were/was consistently found to be phosphorylated in proteasomes isolated from glucose restricted cells, which may be involved in the increased proteolysis capacity of proteasomes from restricted cells. We were not able to observe changes in the gate opening nor in the spatial conformation in 20S proteasome particles isolated from glucose restricted cells, suggesting that the changes in activity were not accompanied by large conformational alterations in the 20S proteasome but involved allosteric activation of proteasome catalytic site.
Delta radiomics analysis for prediction of intermediary- and high-risk factors for patients with locally advanced cervical cancer receiving neoadjuvant therapy
Authors: Wu Rong-Rong , Zhou Yi-Min , Xie Xing-Yun , Chen Jin-Yang , Quan Ke-Run , Wei Yu-Ting , Xia Xiao-Yi , Chen Wen-Juan 
Published: November 2023

AbstractThis study aimed to assess the feasibility of using magnetic resonance imaging (MRI)-based Delta radiomics characteristics extrapolated from the Ax LAVA + C series to identify intermediary- and high-risk factors in patients with cervical cancer undergoing surgery following neoadjuvant chemoradiotherapy. A total of 157 patients were divided into two groups: those without any intermediary- or high-risk factors and those with one intermediary-risk factor (negative group; n = 75). Those with any high-risk factor or more than one intermediary-risk factor (positive group; n = 82). Radiomics characteristics were extracted using Ax-LAVA + C MRI sequences. The data was divided into training (n = 126) and test (n = 31) sets in an 8:2 ratio. The training set data features were selected using the Mann–Whitney U test and the Least Absolute Shrinkage and Selection Operator (LASSO) test. The best radiomics features were then analyzed to build a preoperative predictive radiomics model for predicting intermediary- and high-risk factors in cervical cancer. Three models—the clinical model, the radiomics model, and the combined clinic and radiomics model—were developed in this study utilizing the random forest Algorithm. The receiver operating characteristic (ROC) curve, decision curve analysis (DCA), accuracy, sensitivity, and specificity were used to assess the predictive efficacy and clinical benefits of each model. Three models were developed in this study to predict intermediary- and high-risk variables associated with postoperative pathology for patients who underwent surgery after receiving neoadjuvant radiation. In the training and test sets, the AUC values assessed using the clinical model, radiomics model, and combined clinical and radiomics models were 0.76 and 0.70, 0.88 and 0.86, and 0.91 and 0.89, respectively. The use of machine learning algorithms to analyze Delta Ax LAVA + C MRI radiomics features can aid in the prediction of intermediary- and high-risk factors in patients with cervical cancer receiving neoadjuvant therapy.
Using machine learning approach for screening metastatic biomarkers in colorectal cancer and predictive modeling with experimental validation
Authors: Ahmadieh-Yazdi Amirhossein , Mahdavinezhad Ali , Tapak Leili , Nouri Fatemeh , Taherkhani Amir , Afshar Saeid 
Published: November 2023

AbstractColorectal cancer (CRC) liver metastasis accounts for the majority of fatalities associated with CRC. Early detection of metastasis is crucial for improving patient outcomes but can be delayed due to a lack of symptoms. In this research, we aimed to investigate CRC metastasis-related biomarkers by employing a machine learning (ML) approach and experimental validation. The gene expression profile of CRC patients with liver metastasis was obtained using the GSE41568 dataset, and the differentially expressed genes between primary and metastatic samples were screened. Subsequently, we carried out feature selection to identify the most relevant DEGs using LASSO and Penalized-SVM methods. DEGs commonly selected by these methods were selected for further analysis. Finally, the experimental validation was done through qRT-PCR. 11 genes were commonly selected by LASSO and P-SVM algorithms, among which seven had prognostic value in colorectal cancer. It was found that the expression of the MMP3 gene decreases in stage IV of colorectal cancer compared to other stages (P value < 0.01). Also, the expression level of the WNT11 gene was observed to increase significantly in this stage (P value < 0.001). It was also found that the expression of WNT5a, TNFSF11, and MMP3 is significantly lower, and the expression level of WNT11 is significantly higher in liver metastasis samples compared to primary tumors. In summary, this study has identified a set of potential biomarkers for CRC metastasis using ML algorithms. The findings of this research may provide new insights into identifying biomarkers for CRC metastasis and may potentially lay the groundwork for innovative therapeutic strategies for treatment of this disease.
Blink-related EEG activity measures cognitive load during proactive and reactive driving
Authors: Alyan Emad , Arnau Stefan , Reiser Julian Elias , Getzmann Stephan , Karthaus Melanie , Wascher Edmund 
Published: November 2023

AbstractAssessing drivers’ cognitive load is crucial for driving safety in challenging situations. This research employed the occurrence of drivers’ natural eye blinks as cues in continuously recorded EEG data to assess the cognitive workload while reactive or proactive driving. Twenty-eight participants performed either a lane-keeping task with varying levels of crosswind (reactive) or curve road (proactive). The blink event-related potentials (bERPs) and spectral perturbations (bERSPs) were analyzed to assess cognitive load variations. The study found that task load during reactive driving did not significantly impact bERPs or bERSPs, possibly due to enduring alertness for vehicle control. The proactive driving revealed significant differences in the occipital N1 component with task load, indicating the necessity to adapt the attentional resources allocation based on road demands. Also, increased steering complexity led to decreased frontal N2, parietal P3, occipital P2 amplitudes, and alpha power, requiring more cognitive resources for processing relevant information. Interestingly, the proactive and reactive driving scenarios demonstrated a significant interaction at the parietal P2 and occipital N1 for three difficulty levels. The study reveals that EEG measures related to natural eye blink behavior provide insights into the effect of cognitive load on different driving tasks, with implications for driver safety.
Carbon-infiltrated carbon nanotubes inhibit the development of Staphylococcus aureus biofilms
Authors: Bowden Lucy C. , Evans Jocelyn G. W. , Miller Katelyn M. , Bowden Anton E. , Jensen Brian D. , Hope Sandra , Berges Bradford K. 
Published: November 2023

AbstractStaphylococcus aureus forms biofilms that cause considerable morbidity and mortality in patients who receive implanted devices such as prosthetics or fixator pins. An ideal surface for such medical devices would inhibit biofilm growth. Recently, it was reported that surface modification of stainless steel materials with carbon-infiltrated carbon nanotubes (CICNT) inhibits the growth of S. aureus biofilms. The purpose of this study was to investigate this antimicrobial effect on titanium materials with CICNT coated surfaces in a variety of surface morphologies and across a broader spectrum of S. aureus isolates. Study samples of CICNT-coated titanium, and control samples of bare titanium, a common implant material, were exposed to S. aureus. Viable bacteria were removed from adhered biofilms and quantified as colony forming units. Scanning electron microscopy was used to qualitatively analyze biofilms both before and after removal of cells. The CICNT surface was found to have significantly fewer adherent bacteria than bare titanium control surfaces, both via colony forming unit and microscopic analyses. This effect was most pronounced on CICNT surfaces with an average nanotube diameter of 150 nm, showing a 2.5-fold reduction in adherent bacteria. Since S. aureus forms different biofilm structures by isolate and by growth conditions, we tested 7 total isolates and found a significant reduction in the biofilm load in six out of seven S. aureus isolates tested. To examine whether the anti-biofilm effect was due to the structure of the nanotubes, we generated an unstructured carbon surface. Significantly more bacteria adhered to a nonstructured carbon surface than to the 150 nm CICNT surface, suggesting that the topography of the nanotube structure itself has anti-biofilm properties. The CICNT surface possesses anti-biofilm properties that result in fewer adherent S. aureus bacteria. These anti-biofilm properties are consistent across multiple isolates of S. aureus and are affected by nanotube diameter. The experiments performed in this study suggest that this effect is due to the nanostructure of the CICNT surface.